# RETINA: Distributed and Secure Trust Management for Smart Grid Applications
and Energy Trading

Vaios Boulgouras  Thodoris Ioannidis  Ilias Politis  Christos Xenakis

###### Abstract

The rapid adoption of smart grids demands robust security and efficiency
measures due to their critical role in delivering electricity and their
potential for customer-oriented benefits. This paper presents an innovative
framework, named RETINA, which provides a resilient and secure energy trading
mechanism within smart grid systems. RETINA tackles the inherent security and
infrastructure challenges in smart grids by establishing a trust-based
security layer and facilitating energy transactions through blockchain
technology. Our proposed solution integrates Public Key Infrastructure (PKI)
and the Web of Trust (WoT) concepts, promoting decentralized communication
channels and robust key management. We further introduce a smart contract-
based energy trading mechanism that factors in trust, distance, and energy
type (green or non-green) in cost calculation. The utility and robustness of
RETINA have been validated in a virtualized testbed environment with 500
nodes, demonstrating superior performance in terms of scalability and
resilience compared to the existing WoT scheme. Furthermore, RETINA
successfully enables a secure and efficient energy trading scheme, promoting
the use of renewable energy sources. Future enhancements will include
application to a realistic smart grid deployment and the integration of
additional functionalities. This groundbreaking solution has the potential to
revolutionize the smart grid ecosystem, addressing its current limitations and
propelling the industry towards a future of advanced and secure energy
exchange.

###### keywords:

Smart grids , Trust Management , Blockchain , Security , Energy Trading

††journal: Sustainable Energy, Grids and Networks

[1]organization=Secure Systems Laboratory, University of Piraeus,
country=Greece [2]organization=Industrial Systems Institute, Research Centre
“ATHENA”, country=Greece

##  1 Introduction

Smart grids have become a key focus for delivering electricity in a more
efficient and eco-friendly manner. Recent technological advancements, such as
client-oriented metering mobile apps and provider-oriented data aggregation
software, have contributed to this trend [1]. These advancements offer
environmental benefits and financial advantages to consumers, prosumers (those
who both produce and consume electricity), and energy providers by reducing
operational expenses Operational Expenditure (OPEX) [2]. As critical national
infrastructures [3], smart grids require continuous operation and integrity
protection, making it crucial to implement state-of-the-art security measures.

Robust security measures are essential for smart grids due to their
criticality. Establishing a strong security foundation for financial
transactions and secure operation of smart applications supporting grid
functionalities is mandatory [4]. As smart grids rely on distributed
computing, such as smart meters, information exchange over power lines or
wireless channels is susceptible to security threats. To prevent and mitigate
these threats, security operators propose solutions utilizing advanced
technologies. However, smart grids face technical challenges related to
infrastructure security and network architecture that must be addressed to
fully realize their potential and enable energy exchange among prosumers.

First, the use of certificate authorities Central Authorities (CA) and nodes
in smart grid networks can create single points of failure [5], compromising
system safety and functionality. If the CA fails, communication among smart
grid nodes may be delayed or suspended, significantly impacting performance
and reliability.

Second, while decentralized solutions based on blockchain technology are
gaining popularity for their potential to enhance security and transparency in
smart grid systems, they can also be resource-intensive and contradict smart
grid principles. The maintenance of such solutions can consume significant
electricity [6].

Third, there are concerns about the operational cost of energy trading
solutions built on the Ethereum network, which currently incurs high
transaction fees. This inhibits the adoption of such solutions by providers
and customers, reducing their financial benefits.

Lastly, scalability is critical for widespread energy trading adoption among
prosumers in smart grids. Existing energy trading solutions primarily focus on
small-scale electricity networks, such as microgrids [7]. Scaling up poses
significant challenges due to increased complexity and resource requirements.

One widely adopted solution for establishing trust between grid components is
the Web of Trust (WoT) LABEL:weboftrust. In the context of smart grids, WoT
operates through cryptographic authentication and authorization. Each grid
entity is assigned a digital identity, typically in the form of a digital
certificate or public key infrastructure (PKI) mechanism, to verify the
authenticity and integrity of exchanged data. WoT employs digital signatures
to ensure that only trusted entities participate in communication, protecting
data during transit.

However, WoT also has shortcomings. The process of assigning and managing
digital certificates can be vulnerable to attacks, undermining the trust
foundation. Managing a large number of digital identities and certificates
becomes complex and resource-intensive as the grid expands. Proper key
management, including rotation, revocation, and protection against compromise,
is crucial. Efficient mechanisms for trust revocation are necessary to address
compromises and unauthorized access, ensuring grid security. Finally, WoT
suffers from disturbing the required balance between centralization and
decentralization which is important to avoid single points of failure while
maintaining effective management and coordination. Addressing these challenges
involves robust security protocols, effective key management, standardized
practices and collaboration among stakeholders.

In addition to the security challenges posed by the distributed nature of
smart grids, energy trading among grid participants has also sprouted along
the smart grids. With the smart grid’s ability to perform simple computational
processes on smart meters, which are essentially IoT devices, the role of
energy prosumers has evolved, facilitating the ability to trade energy between
two parties over the grid [8]. Energy exchange infrastructures can emerge
based on this concept, which is pivotal in enabling modern electric grids to
reach their full potential. By aiming for eco-friendly solutions and financial
benefits for users, energy trading adds value to consumers compared to legacy
grids. Additionally, energy trading complements other solutions, such as
pumped storage hydro-power infrastructures [9], that aim to minimize battery
usage for storage purposes by instantly distributing and consuming electricity
to areas in need. Reduced use of batteries and easy access to green sources of
electricity helps decrease the environmental footprint. Moreover, consumers
have a variety of available sources offering energy, allowing them to choose
the most cost-effective one. By adopting energy trading, the incidence of
blackouts due to catastrophic failures in power plants can be significantly
reduced.

This paper introduces a framework that establishes the basis for a secure and
resilient energy trading mechanism, enabling the secure and efficient
operation of smart applications within smart grids. Energy exchange
necessitates a robust underlying architecture that adheres to essential
standards to facilitate the seamless and secure execution of associated
actions. In the absence of those standards, untrusted entities can appear,
posing a risk of dishonest trading and potentially leading to market price
manipulation and disruption of smart grid operations. In smart grid
ecosystems, the concepts of demand and supply play crucial roles. Demand
represents the requirement for additional electricity, while supply refers to
the surplus electricity that can be provided to the grid. These two concepts
are intertwined in a way that they complement each other, offering an
opportunity to fulfill the needs of a smart grid without solely relying on the
traditional provider. Blockchain technology is employed to facilitate this,
leveraging a dedicated smart contract and functionalities that empower
participants to place “buy” or “sell” orders. Blockchain enables transparent
and secure energy transactions within the smart grid ecosystem.

More precisely, the paper focuses on developing a distributed security
platform called RETINA, which aims to provide prosumer-oriented smart grid
environments with robust key management and authentication capabilities. This
platform enables independent and decentralized communication channels within
the smart grid ecosystem. In addition, the proposed solution incorporates a
smart contract-based energy trading mechanism that considers trust, distance,
and the type of energy (green or non-green) as attributes in the cost
calculation. By integrating trust and energy awareness, RETINA enhances
current smart grid implementations. One of the key features of RETINA is its
ability to ensure business continuity even with mitigation failures and
realized risks, allowing participating nodes to continue their operations
securely. Scalability is another vital aspect addressed in the design of
RETINA, recognizing the dynamic and evolving nature of smart grids [10]. With
this in mind, RETINA is designed to be a swift and secure solution that
facilitates secure bidirectional communication among smart grid participants.
To establish a strong security foundation for RETINA’s energy trading
mechanism, an innovative hybrid approach combining the Public Key
Infrastructure (PKI) and Web of Trust (WoT) concepts is employed. This hybrid
solution is further augmented by the utilization of Hyperledger Fabric, an
advanced blockchain framework, enabling feeless and expeditious transactions.
Through the incorporation of Hyperledger Fabric, a decentralized and
distributed ledger technology, trust is upheld among network participants
while mitigating the risk of malicious actions. Through the energy trading
mechanism, prosumers engage in bartering, incentivizing the consumption of
energy generated from renewable sources. Overall, the proposed RETINA platform
integrates security, scalability, and energy awareness to enhance the
functionality and efficiency of smart grids, promoting the adoption of
renewable energy sources within the ecosystem.

In summary, the paper makes the following main contributions:

  * 1.

It introduces RETINA, a novel hybrid approach combining PKI and WoT
architectures on Hyperledger Fabric, enhancing trust through endorsements,
attestation, and the security features of blockchain.

  * 2.

It overcomes challenges related to resource-friendly trust management and
enables fee-less transactions by incorporating a permissioned ledger,
providing an efficient solution for energy trading processes.

  * 3.

It integrates key exchange, trust management, and energy trading, enabling
decentralized participation in green energy production and consumption through
smart contracts and a continuous trust mechanism among smart grid entities.

  * 4.

The outcomes of RETINA are quantified and validated using a virtualized
experimental testbed, demonstrating its superiority over existing trust
management solutions for smart grids.

The remainder of this paper is organized as follows. In Section 8, a
literature review related to RETINA is presented, focusing on infrastructure
security and current energy exchange schemes. The paper’s major innovations
are also summarized in this section. Section 3 provides a detailed description
of the proposed solution’s architecture and functions. In Section 4, a
performance evaluation of the proposed framework is conducted, comparing its
computation and delay efficiency to state-of-the-art solutions from the
literature. Section 5 focuses on the energy trading aspect of the proposed
solution, highlighting the applicability of RETINA. The security risks of
RETINA and their impact are discussed in Section 6. Section 7 critically
appraises the proposed framework, discussing the advantages of the hybrid
trust establishment scheme. Finally, Section 9 concludes the paper.

##  2 Background

In this section the necessary foundational knowledge required to comprehend
the key concepts and technologies associated with RETINA are presented.

###  2.1 Energy Trading

Energy trading among prosumers is a dynamic process that operates on the
principles of supply and demand, where these entities, who both generate and
consume electricity, actively engage in buying and selling electricity based
on their specific production and consumption patterns. In this market,
prosumers have the opportunity to optimize their energy usage and potentially
reap financial benefits by participating as either buyers or sellers,
depending on their current energy requirements.

To initiate the energy trading process, prosumers place orders specifying
their desired quantity of energy to be bought or sold. These orders reflect
their individual needs and preferences, taking into account factors such as
their electricity generation capacity, consumption patterns, and any surplus
or deficit in their energy supply. Through a transparent and efficient
marketplace, these orders are matched with corresponding offers from other
prosumers, facilitating the exchange of electricity between parties. By
actively participating in energy trading, prosumers can effectively manage
their energy resources and optimize their overall energy consumption. For
instance, a prosumer with excess energy generation beyond their own
consumption needs can choose to sell the surplus to another prosumer who
requires additional electricity. Conversely, a prosumer with higher energy
consumption demands than their own generation capacity can purchase the needed
energy from a willing seller. This mutual exchange of electricity enables
prosumers to balance their energy needs, enhance grid stability, and
contribute to the overall efficiency and sustainability of the energy system.

Energy trading among prosumers provides a decentralized and market-driven
approach to electricity exchange, allowing participants to leverage their
individual generation and consumption capabilities. By actively engaging in
buying and selling electricity, prosumers play an integral role in shaping the
energy landscape, fostering renewable energy adoption, and fostering a more
efficient and sustainable energy ecosystem.

###  2.2 Public Key Infrastructure

PKI is employed as a fundamental mechanism for creating and signing
certificates. PKI serves as a trusted framework that facilitates secure
communication and authentication within a smart grid. Each smart meter is
equipped with unique cryptographic keys and digital certificates. These
certificates serve as a form of identity verification and endorsement for the
smart meters. When smart meters interact with each other, they can present
their certificates as a means of mutual authentication. By verifying the
digital signatures of the certificates using the public keys stored on the
blockchain, the smart meters can confirm the identity and trustworthiness of
their counterparts.

The utilization of PKI in this context enables a robust and secure endorsement
process for smart meters. It ensures that only authorized and trusted devices
are involved in energy trading transactions. By relying on the cryptographic
capabilities of PKI, the integrity and confidentiality of communication
between smart meters are protected, safeguarding against unauthorized access,
tampering, or impersonation.

###  2.3 Web of Trust

The utilization of PKI enables the establishment of a Web of Trust, which
facilitates the operation of the system without the need for a central
authority. PKI serves as a foundational framework for creating and managing
trust relationships among the smart meters in a decentralized manner. Through
PKI, a WoT is formed among the smart meters, where each smart meter can verify
the certificates of other smart meters based on the trustworthiness of the
signing authorities. By building and maintaining a network of trusted
relationships, smart meters can operate autonomously and securely without
relying on a central authority for every transaction or communication.

In this WoT, smart meters can validate the digital signatures of certificates
using the corresponding public keys stored in their local trust repositories.
This process allows them to verify the authenticity of the certificates and
the identities of other participating smart meters. The decentralized nature
of the WoT enables smart meters to establish and manage trust relationships
among themselves. As smart meters interact and engage in energy trading
processes, they can evaluate the trustworthiness of their counterparts based
on the reputation of the signing authorities and the history of successful
interactions. By leveraging PKI to create a Web of Trust, the energy trading
system achieves a resilient and secure operation without relying on a central
authority. This decentralized trust model ensures that only trusted smart
meters are involved in transactions, mitigating the risks of malicious
activity and unauthorized access.

###  2.4 Blockchain and Distributed Ledgers

The blockchain technology, specifically the Hyperledger Fabric platform, is
employed to establish two immutable and transparent ledgers that record the
endorsed certificates. Each smart meter’s signed certificate, representing the
endorsement of its identity and trustworthiness, is stored in one of those
distributed ledgers. The blockchain ensures the integrity and tamper-
resistance of the endorsements, as any modification or tampering attempts
would be immediately detectable through consensus mechanisms and cryptographic
hashes. The second ledger, utilized for trading orders, facilitates the
exchange of energy among prosumers. It serves as a decentralized platform
where participants can place their orders to buy or sell electricity based on
their production and consumption needs. By leveraging blockchain and
distributed ledgers, RETINA provides several key benefits. Firstly, the
immutability of the blockchain ensures the integrity of the stored
certificates and trade orders, and prevents unauthorized modifications,
enhancing the overall security of the system. Secondly, the distributed nature
of the ledger eliminates the reliance on a centralized authority, enabling
decentralized and autonomous energy trading. Thirdly, the transparency of the
ledger allows participants to verify the validity of certificates and track
the history of transactions, promoting trust and accountability.

The separation of the two ledgers in RETINA ensures a clear distinction
between the storage of certificates (endorsements) and the trading orders.
This design choice allows for efficient management and retrieval of
endorsements while providing a dedicated platform for energy trading
operations. The certificates ledger serves as a foundation for establishing
trust among smart meters, while the trading orders ledger enables the secure
and transparent exchange of electricity among prosumers.

###  2.5 Threat Model

In the context of RETINA and its energy trading system, it is important to
consider a threat model that includes potential malicious actors attempting to
manipulate the price of electricity. Malicious actors who may disseminate
false or misleading information about energy production or consumption to
create a false perception of scarcity or abundance are considered. This can
lead to market participants making uninformed decisions and potentially
manipulating the electricity price. Furthermore, malicious actors may attempt
to compromise the integrity or accuracy of smart meters deployed within the
network. By tampering with the measurement or reporting capabilities of these
devices, they can manipulate the energy consumption or production data,
leading to distorted market conditions and price manipulation.

##  3 Architecture

The architecture of the proposed framework follows a “bottom-up” approach,
beginning with analyzing the smart grid architecture and the role of
blockchain. The goal is to establish trust among the network elements and to
create a secure and decentralized environment. To achieve this, a hybrid
approach that combines the concepts of PKI and WoT is employed, augmented with
blockchain. The PKI infrastructure is leveraged to incorporate certificates,
which attest to the trustworthiness of individual network nodes. However,
instead of relying solely on certificates issued by a centralized certificate
authority, the proposed architecture promotes the creation of a Web of Trust
among all network nodes. This means that the entire network endorses and
recognizes certificates rather than a single authority. This distributed
approach ensures the network’s resilience if certificate authorities
(empowered nodes) become unavailable. In addition, the blockchain technology
is crucial in enhancing the security of the smart grid architecture. It
provides an immutable and transparent ledger to store the certificates
securely. By logging the certificates on the blockchain, their integrity and
authenticity can be verified by any participant in a tamper-resistant manner.

The capabilities of RETINA are further extended by incorporating an energy
trading mechanism. This mechanism is built on the secure and trusted
environment established through the WoT, reflected in the ledger entries. Like
the trust establishment process, blockchain ensures the immutability and
transparency of energy production and consumption activities. These activities
are logged on the blockchain, enabling accurate and verifiable customer
billing. By integrating the secure and trusted environment of RETINA with the
energy trading mechanism supported by blockchain, the proposed framework
provides a robust and transparent infrastructure for smart grid operations. It
leverages the inherent characteristics of blockchain, such as immutability and
transparency, to enhance the security and reliability of the smart grid
architecture, ultimately benefiting both consumers and energy providers.

###  3.1 RETINA Smart Grid and Blockchain Architecture

The proposed smart grid infrastructure, as illustrated in Figure 1,
constitutes of three main components: $(i)$ energy provider, $(ii)$ empowered
nodes, and $(iii)$ prosumers’ smart meters. The energy provider includes
various entities such as energy plants, administration systems, and billing
systems. They play a pivotal role in managing and providing energy to the
grid. The empowered nodes are strategically positioned in the network to
ensure its robustness and mitigate the risk of a single point of failure. Each
empowered node defines a neighborhood representing a distinct administrative
area within the smart grid. By compartmentalizing the network, administrative
responsibilities and resources are distributed among multiple empowered nodes,
enhancing the resilience and security of the overall system. Finally, the
prosumers’ smart meters are key elements in the smart grid infrastructure.
They enable measuring and monitoring energy consumption and production at the
individual prosumer level. These smart meters interact with the empowered
nodes and participate in the secure communication channels established within
the framework.

Figure 1: RETINA as an overlay framework, where network participants possess
their own certificates, signed by nodes that endorse them

RETINA is depicted as an overlay framework on top of the energy grid in Figure
1. It utilizes blockchain to provide a secure infrastructure to establish
communication channels and gateways. These channels facilitate inter-
neighborhood connections, enabling access to a larger market with multiple
electricity buying and selling offers. By leveraging the blockchain, RETINA
ensures the integrity and transparency of the communication infrastructure.
Further, the PKI concept is employed on top of the blockchain to facilitate
the issuance and management of personal certificates for each smart meter.
These certificates serve as a means to establish trust and accumulate
endorsements from other participants in the grid. This process creates a WoT,
where data exchange can occur securely with trusted entities. One of the
advantages of this infrastructure is its resilience in the face of empowered
node failures. Even if an empowered node becomes unavailable, the grid can
continue its operations due to the trust relationships established among the
network participants. These relationships are reflected in the Distributed
Ledger (DL), ensuring the continuity and reliability of the smart grid.

As shown in Figure 2, each smart meter in the smart grid system possesses a
Secret/Public (Sk/Pk) key pair, along with its associated certificate. To
ensure the security of cryptographic operations and protect the secret key, a
secure Trusted Execution Environment (TEE) is utilized within each smart
meter. Additionally, each smart meter maintains a partial copy of the trust
management ledger. This ledger contains relevant information about the trust
relationships and endorsements among the network participants. Having a
partial copy of the ledger enables smart meters to assume the corresponding
duties and responsibilities in case an empowered node becomes compromised or
unavailable. This feature enhances the resilience and continuity of the
system. In essence, the empowered nodes play a paramount role in the
blockchain infrastructure. They host the ledgers and smart contracts necessary
for the operation of the smart grid system. They are also responsible for
resource-intensive operations such as consensus, transaction processing, and
executing smart contracts. By distributing these tasks among multiple
empowered nodes, the system achieves higher scalability and resilience.
Finally, the energy provider, depicted in the diagram, receives information
from the empowered nodes for billing and management purposes. It utilizes the
data collected from the smart meters and processed by the empowered nodes to
calculate and manage energy consumption, billing, and other administrative
tasks within the smart grid system.

Figure 2: Resources and operations within the RETINA network components

The blockchain possesses vital characteristics that ensure robust security,
accountability, and non-repudiation. Moreover, its immutability guarantees the
creation of indisputable records. The operational functionalities of the
empowered nodes encompass the execution of smart contracts and the maintenance
of up-to-date ledgers. As a decentralized node certificate storage platform,
the blockchain facilitates energy exchange, where two smart contracts are
deployed, and corresponding ledgers are formed, as depicted in Figure 3. To
establish a secure foundation for the smart grid, the ledger is consistently
updated whenever a new trust relationship is established, or an existing one
is revoked. Figure 3 presents a snapshot of the Trust Ledger, illustrating the
bidirectional trust relationship between smart meter $A$ and smart meters $B$
and $D$. The smart contract securely maintains this trust relationship, which
automates and safeguards energy transactions for the energy trading mechanism
of RETINA, encompassing “buy” and “sell” orders. The outcomes of completed
transactions are accurately recorded on the ledger, ensuring transparency and
accountability.

Figure 3: RETINA smart contracts and Ledgers residing on the empowered nodes

Selecting a consensus algorithm for a blockchain infrastructure is critical,
as it significantly impacts system performance and financial implications. In
this scheme, the Proof-of-Authority (PoA) consensus algorithm [11] has been
chosen for utilization by the empowered nodes to achieve consensus and record
information on the ledgers. PoA is advantageous due to its minimal
computational resource requirements, resulting in low energy consumption
during operation. The PoA consensus mechanism relies on a limited number of
validators to approve transactions for ledger entry. This enables frequent
updates to the blockchain, reduces the time between block creation, and
facilitates the processing of numerous transactions within short timeframes.
The scalability of PoA is particularly beneficial for smart grids, where the
network size may vary and potentially increase substantially. In RETINA, the
verification of blocks and transactions is carried out by the empowered nodes,
who assume the responsibility of maintaining the blockchain infrastructure.

###  3.2 Key Management and Authentication

The security of the RETINA platform rests on two fundamental pillars: $(i)$
key management operations and $(ii)$ authentication of network entities. These
pillars exclude untrusted entities from all network communications and energy
trading operations, effectively mitigating the risk of fraudulent activities.
The following functionalities are instrumental in realizing this secure
scheme.

####  3.2.1 New Smart Meter Joining the Smart Grid

The process followed by a new node to join the network is illustrated in
Figure 4. In order for a new node to join a smart grid that incorporates the
RETINA authentication scheme, it must acquire a signature from at least one
empowered node with a valid certificate that is already part of the network,
as shown in 1. When a node intends to join the network for the first time, it
generates a key pair consisting of a Public key ($P_{k}$), a Secret key
($S_{k}$), and a corresponding self-signed certificate. Subsequently, the new
node initiates a request to join the network. A remote attestation procedure
is then conducted by the empowered node responsible for the respective
neighborhood. This attestation verifies that the candidate node is utilizing
provider-approved software and has not been tampered with or subjected to
unauthorized alterations. If the remote attestation yields a positive result,
the empowered node acting as an introducer signs the certificate of the new
node. This signed certificate is logged in the Distributed Ledger (DL) along
with the corresponding identification number of the new node, denoted as
$ID_{n}$ (where $n\in[1,N]$, and $N$ represents the network size). In 1, the
certificate format is depicted. The Public key ($P_{k}$) is publicly available
for all-access, followed by its owner’s address (Node $A$). The first
signature accumulated originates from the self-signing step, which precedes
the endorsement from an empowered node. Lastly, a signature from Node $B$
follows, establishing a trust relationship between Nodes $A$ and $B$.

Figure 4: Node join operation

⬇

Pk 2048R/678455A3 2022-02-07 [expires: 2023-06-07]

uid Node A<EMAIL_ADDRESS>
sig 962789D1 2023-02-07 Node A<EMAIL_ADDRESS>
sig F4V7287Z 2023-02-07 Empowered<EMAIL_ADDRESS>
sig A55CDCC1 2023-02-07 Node B<EMAIL_ADDRESS>
Listing 1: Format of the certificate

The new node engages in certificate signature exchanges with the nodes
residing in the $2^{x}$ network positions, where $0\leq x\leq N/4$, as
depicted in Figure 5 for Nodes $A$ and $J$. This approach is not employed
arbitrarily but is inspired by the demonstrated effectiveness of Distributed
Hash Table (DHT) routing algorithms in establishing communication channels
among nodes that are not necessarily directly connected [12, 13]. This
eliminates the need for a new node to exchange and store signatures from all
other network nodes. In contrast, in a traditional WoT network, each node must
exchange signatures with all other participants. The utilization of DHT-based
routing algorithms simplifies the process and reduces the signature exchange
requirements for new nodes, allowing them to establish trust relationships
with a subset of nodes within the network.

Figure 5: A random snapshot of the process of exchanging signatures, depicting
the connections that Nodes $A$ and $J$ make with the nodes that reside on the
$2^{N}$ network positions

The newly signed certificates are stored locally on the smart meter and the
empowered node. To avoid unnecessary storage, simple network nodes maintain
only the portion of the ledger corresponding to the endorsements they have
given and received. In contrast, empowered nodes possess the complete version
of the ledger, including the entire network’s trust relationships. Partial
ledgers maintained by simple nodes are not actively used during normal
operations but are stored and updated. This storage approach ensures that
simple nodes do not need to store and manage the entire ledger, reducing their
storage requirements. However, they retain the information related to their
endorsements and received certificates, enabling them to validate trust
relationships when required. If all empowered nodes in a neighborhood are
compromised, simple nodes have the potential to assume the elevated
responsibilities and role of an empowered node. This ensures the continuity of
network operations and the preservation of trust within the neighborhood, even
in the face of compromised empowered nodes.

In addition to new nodes, previous network participants who may have gone
offline have the potential to rejoin the smart grid, as depicted in Figure 4.
In such cases, if the certificate previously used by the participant is still
valid and has not been revoked or expired, no further action is required. The
participant can use its existing $ID_{n}$ and the corresponding certificate
already stored on the DL. However, if the old certificate is no longer valid,
the participant must repeat the aforementioned process of joining the network.
To ensure the seamless reintegration of participants who have left the smart
grid network and to enable participants with expired or revoked certificates
to regain access, a comprehensive procedure is implemented. This procedure
involves the generation of a new key pair, obtaining a signature from an
authorized node, undergoing remote attestation, and acquiring a newly signed
certificate that is recorded on the distributed ledger (DL). By following this
process, the smart grid guarantees that participants with valid previous
certificates can easily rejoin the network, while also ensuring that those
with expired or revoked certificates must go through the necessary steps to
regain network access.

####  3.2.2 Establishing Trust Relationships

In a smart grid ecosystem, devices inherently execute applications that
require communication among the network’s participants. To ensure the smooth
execution of these applications, a reliable trust system is necessary. This is
achieved by leveraging the initial signature(s) acquired by a new node from
the empowered nodes that introduced it to the network. As smart applications
are utilized, communication is attempted with other nodes, resulting in an
exchange of certificate signing among the network’s entities. As mentioned
earlier, every new node joining the network, as well as nodes rejoining the
smart grid, possesses a certificate signed by one or more empowered nodes.
Using this certificate, additional signatures are acquired from common nodes
residing in the $2^{x}$ positions (as indicated by the last signature in 1). A
smart contract is employed to facilitate this process. For instance, if Node
$A$ has been introduced to the network by Empowered Node $S$, the smart
contract will utilize Node $A$’s certificate endorsement by Node $S$ to
introduce itself to other nodes that Node $S$ has also introduced. This
introduction lets the nodes exchange signatures by signing each other’s
certificates. Normal communication within the smart grid, driven by the
operational requirements of smart applications, relies on the trust
established through these mechanisms. The trust serves as a foundation for
establishing the desired relationships among network participants, allowing
for effective and secure communication.

In scenarios where specific empowered nodes (i.e., introducers) are
unavailable, and there is no direct trust path between two nodes (i.e., they
have not previously signed each other’s certificates), the smart contract
initiates a process of indirect trust establishment. To provide a clearer
understanding of the procedure followed by the smart contract in establishing
trust relationships, Figure 6 is provided. The following example illustrates
the actions taken when Node $A$ aims to establish a trust relationship and
communicate with Node $B$:

Figure 6: Trust establishment

Step 1. Node $A$ first checks its own certificate to see if it has an existing
endorsement from Node $B$. If such an endorsement exists, the process is
completed at this point, and Node $A$ can establish a trust relationship with
Node $B$.

Step 2. If Node $A$ does not find an endorsement from Node $B$ in its own
certificate, a Certificate Lookup procedure is initiated. This procedure aims
to find the certificate of Node $B$, denoted as $Cert_{B}$.

Step 3. Node $A$ examines the trustworthiness of the endorsers of $Cert_{B}$.
If any of the endorsers of $Cert_{B}$ are trusted by Node $A$, such as Node
$C$, this information is communicated to Node $B$. Both Node $A$ and Node $B$
then sign each other’s certificates, log the new trust relationship on the
Trust ledger, and conclude the procedure. In this case, only one intermediate
entity, Node $C$, is involved in establishing the trust relationship between
Node $A$ and Node $B$.

Step 4. If no trusted endorsers of Node $B$ are found in Step 3, the
Certificate Lookup procedure continues by exploring the signatures collected
by the certificates of endorsers of Node $B$. For example, unlike Step 3, Node
$A$ does not initially trust Node $C$. However, while searching for a trusted
entity in the signatures of the nodes’ certificates that have endorsed Node
$B$, Node $A$ discovers that Node $D$ has signed the certificate of Node $C$.
This finding establishes a trust path to Node $B$ through Node $D$. Therefore,
the formed chain of trust, in this case, would be $A\Rightarrow D\Rightarrow
C\Rightarrow B$.

In scenarios where Node $D$ initially lacks trust from Node $A$, Node $A$ can
actively search for trusted endorsers of Node $D$ and expand the trust path
accordingly. This iterative process continues until a trusted entity is
discovered or until a predefined maximum chain length is reached. It is
important to note that the performance of the trust establishment procedure,
including delays and success probability, can be influenced by the chosen
maximum chain length within the RETINA system.

The maximum chain length determines the number of intermediate entities or
endorsers that can be explored in the search for a trusted path between nodes.
A longer chain length increases the likelihood of finding a trusted path as
more intermediate entities are considered. However, it also introduces
additional delays in the trust establishment process, as each step
necessitates further verification and validation of the endorsers. Conversely,
a shorter chain length reduces delays but may limit the probability of finding
a trusted path in certain scenarios.

Determining the optimal maximum chain length requires striking a balance
between the desired success rate of trust establishment and the acceptable
delay in the process. This decision should consider the specific requirements
and constraints of the smart grid ecosystem, including network size, the
trustworthiness of entities, and performance considerations. Evaluating and
optimizing the maximum chain length in RETINA is crucial to achieve efficient
trust establishment while meeting the security requirements of the smart grid
network.

####  3.2.3 Certificate Lookup

The Trust DL employed in the RETINA blockchain implementation is distributed
across all network participants. Each participant stores their established
trust relationships locally, while the empowered nodes maintain a complete
copy of the Trust DL. The primary purpose of the Trust DL is to facilitate the
certificate lookup procedure, which occurs on the empowered nodes when a
direct trust relationship is not present but is desired. To perform the
certificate lookup procedure, the empowered nodes utilize the process outlined
in Section 3.2.2. This process identifies the nodes that should be considered
when finding a trust path between two unrelated nodes. As previously
explained, trust paths can be established indirectly through multiple
intermediate nodes. This, combined with the fact that the Trust DL is
processed locally on the empowered nodes, offers several advantages:

  * 1.

RETINA’s swiftness is not limited by network constraints that may be presented
due to bandwidth limitations or increased overhead because of heavy traffic.

  * 2.

The network load will not be burdened with extra traffic due to the
certificate lookup operation, which will be executed locally.

Figure 7 represents a visual depiction of an instance found in every node’s
locally stored Trust DL. This simplified representation illustrates an
already-formed WoT among seven nodes. Each node’s certificate contains
multiple accumulated signatures, establishing new trust relationships. In this
instance, Node $A$ has exchanged signatures with Nodes $B$, $C$, and $F$, as
indicated by the signatures in their respective certificates. Likewise, Nodes
$B$ and $C$ have established trust paths with other nodes. Node $B$ has trust
paths with Nodes $A$, $D$, $E$, and Node $C$ has trust paths with nodes $A$,
$E$, $F$, and $G$. This visualization of the trust relationships showcases the
interconnected nature of the trust paths. It highlights how trust can be
established indirectly through the involvement of intermediate nodes. The
Trust DL stored on each node enables the identification and utilization of
these trust paths to facilitate secure interactions and transactions within
the blockchain network. Overall, this graphical representation demonstrates
the practical application and effectiveness of the Trust DL in enabling trust
establishment and verification between nodes in the RETINA blockchain
implementation.

Figure 7: Snapshot of the Trust Paths that have been formed among seven
network participants

To better understand the Lookup Procedure, an example based on Figure 7 is
presented. In this scenario Node $A$ needs to contact Node $E$. The following
actions will be performed:

Step 1. The initial search focuses on the signatures that $Cert_{A}$ has
accumulated in order to determine whether the target Node $E$ has already
signed it or not.

Step 2. In this scenario Nodes $A$ and $E$ have not exchanged signatures yet,
so a search for trust with one intermediate node commences by examining the
endorsers of Node’s $E$ certificate.

Step 3. The inquiry of Step 2 returns a positive result, as Node $B$, which is
trusted by Node $A$, is an endorser of $Cert_{E}$. At this point the lookup
procedure is concluded successfully and the process to establish a trust
relationship by exchanging signatures, as described in the previous section,
commences.

Following the same train of thought, if the target node was at the next level
in terms of depth, the procedure’s execution would be extended, and an
additional intermediate would be included in the formed trust path. Due to the
nature of the network’s ring-like structure, similar to the one found in DHT
networks, an iterative-recursive hybrid approach [14] was utilized in terms of
search routing, benefiting the overall performance of the system as showcased
in Section 4 below.

####  3.2.4 Certificate Revocation

Node certificates may be revoked for two main reasons. Firstly, a node may
voluntarily leave the network and choose to revoke its certificate. Secondly,
a node might be considered untrustworthy or potentially malicious. To ensure
the integrity of the network, all participating entities undergo periodic
remote attestation conducted by empowered nodes. As described by Panos et al.
[15], this attestation process involves generating a hash value from each
reviewed node’s TEE. This hash value is derived from predetermined software
components and parameters that should remain unchanged. If most nodes
conducting the remote attestation procedure conclude that a particular node’s
software has been tampered with and could potentially engage in malicious
actions, its corresponding certificate is revoked. For instance, in Figure 7,
if $Cert_{B}$ is revoked, the associated signatures in $Cert_{A}$, $Cert_{D}$,
and $Cert_{E}$ would be removed. This revocation process also applies to
empowered nodes to safeguard the smart grid against malicious actors.
Irrespective of whether the revoked certificate belongs to an empowered or a
common node, the network’s operations remain unaffected due to the existing
WoT, which interconnects all smart grid nodes directly or indirectly. In the
aforementioned example, the revocation of $Cert_{B}$ as an intermediate
certificate between Nodes $A$ and $E$ can be compensated by Nodes $C$ and $F$.
Furthermore, the revoked certificate will not be utilized in any future
attempts by other nodes to establish trust relationships among themselves.

Once a certificate revocation occurs, the trust relationships the revoked node
establishes become unavailable if the node later rejoins the network. In such
cases, the procedure for a new smart meter joining the grid must be repeated
only after addressing the compromised software that initially led to the
node’s exclusion from smart grid operations. This entails issuing a new pair
of keys and the associated certificate. Conversely, nodes that abruptly depart
from the smart grid due to Internet connection issues or technical problems do
not need to repeat the join process since their certificate remains valid.

The certificate revocation process is inherently sensitive due to potential
abuse, which could lead to denial of service. To mitigate this risk, the
remote attestation performed by empowered nodes to network participants is
securely protected and inaccessible to users or third parties. This
safeguarding is achieved by utilizing TEE technology, which masks and shields
these operations from malicious actors. The calculation of attestation hashes
from the attestee, and the verification process conducted by the attesters
occur within this protected environment, rendering them immune to tampering by
any entity. Additionally, cryptographic processes related to certificate
signing and energy trading rely on TEE utilization to mitigate various risks
associated with fraudulent activities.

##  4 Performance Evaluation

The proposed framework has undergone rigorous testing and validation across
various scenarios, comparing it to state-of-the-art solutions in terms of
communication and computational costs during trust establishment. A comparison
against Web of Trust (WoT) implementations confirms that RETINA significantly
improves the time required to establish trust in scalable smart grid
environments and demonstrates superior responsiveness when empowered nodes are
lacking. To demonstrate the practicality of RETINA in real-world scenarios,
performance evaluation has been extended to validate an energy trading scheme
that utilizes RETINA to establish trusted nodes as energy traders. This scheme
ensures security guarantees in cases of trust revocation or unauthorized
access by malicious traders. The evaluation of the RETINA-based energy trading
scheme focuses on examining energy trading price fluctuations resulting from
tampering by malicious nodes. Through these evaluations, the framework’s
reliability, efficiency, and security in trust establishment and energy
trading scenarios are demonstrated, providing compelling evidence of its
applicability and effectiveness in real-world deployment.

###  4.1 RETINA Configuration

The simulation of the RETINA framework was deployed on a physical machine
running Ubuntu 18.04 LTS, equipped with an Intel i7 6700HQ processor and 32
gigabytes of RAM. The implementation was carried out in Java, utilizing smart
contracts for Key management and Energy trading functionalities as the main
components. To facilitate the blockchain deployment of RETINA, the Hyperledger
Fabric framework was employed with the assistance of the Hyperledger fabric-
gateway-java dependency. Multiple nodes were simulated to assess the network’s
performance and responsiveness in various real-life scenarios. Each node was
assigned corresponding certificates and wallets for these simulations and
evaluations. The certificates adhere to the PGP standard and employ the SHA-1
hash function, which generates block hashes.

###  4.2 Communication Cost and Computation Time

As depicted in Table 1The evaluation of RETINA primarily centers around its
comparison to related works, specifically regarding two key factors: $(i)$
computation time required for signature exchange between two nodes, and $(ii)$
communication costs associated with the data transferred during the mutual
endorsement process between network nodes. These evaluation criteria aim to
assess the performance and efficiency of RETINA to similar approaches in the
field.

Table 1: Comparison in terms of communication cost and computation time
between RETINA and other similar solutions

Frameworks | Computation Time (ms) | Communication Cost (bits)
---|---|---
FeneChain [16] | 2000 | 540.67
SURVIVOR [17] | 117.35 | 448
BEST [18] | 35 | 961
Secure ET in DRM [19] | 33 | 968
EnergyChain [20] | 33 | 576
RETINA | 19.2 | 192

To calculate the computation time, we measured the duration of various
blockchain-related operations necessary for establishing trust. These
operations encompassed the following:

  * 1.

VerifyCertificate: Use the certificate’s Public key (Pk) to decrypt and verify
its validity. For RETINA, the average time to decrypt and validate the
certificate was $2.7ms$.

  * 2.

SignCertificate: Use own Secret key (Sk) to sign a certificate. In RETINA, the
time required to sign the certificate was calculated at $2.7ms$ on average.

  * 3.

Addition: Making a new entry on the DL (addToDL). On average, the time
required for this process in RETINA is measured at $1ms$.

  * 4.

One-way hash function (SHA-1): Hashing the information pertaining to a new
block (hashData). The SHA-1 operation required in RETINA an average of
$2.7ms$.

  * 5.

Append: Collecting data into a single string, giving it a proper form to
introduce it to the blockchain (addNonce). The append operation in RETINA has
been timed at $0.5ms$ on average.

We obtain the computation time denoted as $CT$ by summing the average times
for each operation. Since the endorsement process for establishing a trust
relationship is executed mutually from both ends, the entire process is
performed twice, once for each node involved. Therefore, we calculate the
total Computation Time as $CT_{total}$ by doubling the computed value of $CT$.
This accounts for the bidirectional nature of the endorsement process,
ensuring a comprehensive evaluation of the computational efficiency of RETINA
in establishing trust between network nodes.

$\small
CT=\texttt{VerifyCertificate}+\texttt{SignCertificate}+\texttt{addNonce}+\texttt{hashData}+\texttt{addToDL}$
$\small CT_{total}=2CT$

The communication cost ($CC$) in the case of RETINA is evaluated based on the
number of bits transferred during the establishment of a trust relationship
between two nodes. In this context, we consider the specific components
involved in the process:

  * 1.

Block Header Size: The number of bits processed at the block header, denoted
as $Hb$, is calculated as: Hb = [32 bits Identity + 256 bits previous block
hash + 32 bits transactions] = 320 bits.

  * 2.

Hash Output: Utilizing the SHA-1 hash function, the output size of the hash,
denoted as $Hout$, is determined as Hout = SHA-1(320 bits + 32 bits nonce + 64
bits padding) = 416 bits.

  * 3.

SHA-1 Input and Digest Size: The total input size for the SHA-1 algorithm is
416 bits, and after digesting, the final output size is 160 bits.

Based on these calculations, the total cost of the PoA consensus algorithm is
determined as PoA = 32 bits Identity + 160 bits SHA-1 digest = 192 bits. It is
important to note that this communication cost is borne solely by the
Empowered nodes due to the nature of the PoA consensus algorithm implemented
in RETINA.

$\small CC=\texttt{ID}+\texttt{SHA-1 digest}$

###  4.3 RETINA Compared to Web of Trust

An infrastructure based on the WoT was implemented, drawing from the
descriptions outlined in the OpenPGP standard [21] and the corresponding
official guide [22]), as a decentralized trust model. This implementation
enables a comparative performance analysis between RETINA and WoT,
highlighting the distinct advantages of each solution. Specifically, we
examine the decentralized performance of RETINA’s algorithm in contrast to a
traditional WoT network, focusing on the time required for $(i)$ introducing a
new node to the network and $(ii)$ establishing communication between two
network participants. Notably, previous literature has conducted network
experiments in similar scenarios involving network sizes ranging from 100 to
500 nodes [23, 24, 25]. To ensure comparability with these studies, our
performance evaluation encompasses network sizes of 100, 200, 300, 400, and
500 nodes.

Figure 8 demonstrates the substantial performance advantage of RETINA over a
traditional WoT network when it comes to the initialization of new network
nodes, as indicated by the introduction times ranging from $1.2ms$ to $2.7ms$
for RETINA, compared to the considerably longer durations of $21.4ms$ to
$144.7ms$ required by a node joining a WoT network. This discrepancy in
performance can be attributed to the distinct mechanisms employed by each
system. In RETINA, a new node only needs to exchange signatures with the nodes
occupying the $2^{x}$ positions, whereas, in a WoT network, the new node must
introduce itself to all other nodes through a flooding procedure.

Figure 8: Comparison in terms of time required for a node to establish a new
trust relationship with a random node under RETINA and WoT schemes, for
different network sizes

While RETINA demonstrates superior performance during the introduction phase
of new nodes, there is a slight trade-off regarding trust establishment, as
illustrated in Figure 9. In a WoT network, a node needs to query its database
to locate the endorsement for another node, whereas, in RETINA, this may not
always be necessary. If the endorsement is not locally stored on a node, a
search is initiated using trust relationships established by other trusted
nodes. However, thanks to RETINA’s recursive/iterative hybrid search method,
the time delay for establishing a trust relationship remains relatively low,
comparable to that of a WoT node. It is important to note that this metric
applies explicitly to a decentralized RETINA scenario, where the empowered
node is unavailable. In other cases, RETINA’s performance closely aligns with
that of a CA-centered network, resembling the WoT approach, as both involve
searching a single database.

Figure 9: Comparison in terms of time required for a new node to join the
network and establish trust among the first tier nodes under RETINA and WoT
schemes, for different network sizes

##  5 Energy Trading

To comprehensively illustrate the benefits of the proposed framework and
demonstrate the practicality of RETINA, we integrated an energy trading
mechanism for smart grids. This mechanism empowers all participating entities,
predominantly prosumers, to engage in buying or selling the energy they
generate within the smart grid ecosystem. By establishing an exchange platform
among these entities, we facilitate increased consumption of green energy.
This is achieved through the availability of diverse energy sources and the
seamless accessibility provided by the trading mechanism. Consequently,
integrating RETINA enables a more sustainable and environmentally friendly
utilization of energy resources within the smart grid infrastructure.

###  5.1 Energy Trading Mechanism

Within RETINA, every network node possesses a wallet that contains the
quantity of produced energy and a corresponding balance. The energy trading
mechanism implemented in RETINA leverages the trust relationships formed
during the earlier stages of the nodes’ life cycle. All entities involved in
the exchange processes are considered trusted, indicating that their
certificates have received one or more signatures from valid endorsers. This
reliance on established trust ensures the integrity and reliability of energy
transactions within the network, fostering a secure and efficient energy
trading environment.

The “buy” and “sell” orders within the energy trading mechanism are posted on
the blockchain and signed by the entities issuing them. This approach ensures
that the orders are openly accessible to all participants in the network,
allowing for easy verification of their authenticity. These orders possess
specific characteristics, including:

  * 1.

kW: The amount of energy to trade.

  * 2.

Production method ($CO_{2}$ footprint): It states whether the power in kW
referred to in an order has been produced using renewable energy sources or
not.

  * 3.

Location: It refers to the smart grid location, in terms of neighborhood, of
the order originator.

Defining the $Price/kW$ in the energy trading mechanism is not deterministic
and considers the aforementioned characteristics, which can vary between
nodes. This architecture is flexible and can accommodate various pricing
models. For the described energy trading scheme, a theoretical pricing model
has been chosen, incorporating the listed criteria through the utilization of
two weights: $a\in[0.2,0.5]$ to account for the trading of green energy (where
a lower $a$ value corresponds to a higher proportion of green energy being
offered), and $b\in[0.2,0.5]$ to account for the distance between the trading
nodes (with a higher $b$ value indicating a greater distance). It should be
noted that the specific values of these weights are merely indicative and can
be adjusted according to the policies of the energy provider. Thus, the
theoretical price assigned to the energy trading contract between two nodes in
the grid can be calculated using the following formula, where StartingPrice
represents the base price per $kW$.

$\small Price=StartingPrice+a(StartingPrice)+b(StartingPrice)$ (1)

During periods of high load on the grid’s infrastructure, prices within the
energy trading mechanism may favor participants who exchange energy with
nearby counterparts within the same neighborhood. This approach helps minimize
the utilization of network resources, and it can be achieved by setting a
minimum value for the “location proximity” weight, thereby reducing the
corresponding energy cost accordingly. To illustrate this concept, consider
the following example, highlighting how the cost of 1kW of energy can vary
based on its specific traits. It is important to note that additional factors,
such as the scarcity of electric power during peak hours, can also be
considered in the price calculation, adhering to the fundamental principles of
supply and demand.

Consider the example of 1kW of energy (with a base price of €1/kW) produced
from renewable energy sources (where $a=0.2$) originating from a node located
in a different neighborhood (with $b=0.5$). In this scenario, the indicative
price of the energy transaction can be calculated using Equation 1, resulting
in $Price=1+1\times 0.2+1\times 0.5=1.7$. Therefore, the calculated price for
this particular energy transaction would be €1.7.

Consider now the case of 1kW of energy (with a base price of €1/kW) generated
from renewable energy sources (with $a=0.2$) originating from the same
neighborhood (with $b=0.2$). Using the same calculation as in Equation 1, the
price for this transaction, accounting for the impact of distance, would be
$Price=1+1\times 0.2+1\times 0.2=1.4$. Therefore, the calculated price for
this specific energy transaction would be €1.4.

In the energy trading mechanism, the nodes automatically place orders based on
the status of their individual energy reserves. A broker, represented by an
algorithm running on the smart meters, considers multiple variables to
determine whether it is necessary to place either “sell” or “buy” orders.
These variables include the current rates of electricity production and
consumption and the availability of battery reserves. By analyzing this data,
the broker creates a projection regarding the potential need or surplus of
electricity. Moreover, the broker considers behavioral patterns observed in
the past, such as increased electricity demand at noon. Based on these
considerations, the broker places the corresponding orders on the ledger.

The energy trading smart contract then takes control, matching “buy” and
“sell” orders that complement each other. The smart contract ensures that the
conditions of each order are met before executing the transaction.
Additionally, it should be noted that the broker can also receive manual input
from the user. This enables the fulfilling of specific needs that may arise
and cannot be anticipated solely by the broker’s algorithm. Once a transaction
is completed, the result is recorded on the ledger, including the updated
values of the remaining energy and balance of the node involved in the
transaction. This logging process ensures transparency and accountability
within the energy trading system.

Algorithm 1 Trading smart contract

1:if $EnergyReserves=HIGH$ then

2: $Action\leftarrow SELL;$

3:else if $EnergyReserves=LOW$ then

4: $Action\leftarrow BUY;$

5:end if

6:if $Action=SELL$ then

7: for $everyBuyorder$ do

8: $GetStartingPrice;$

9: $Price=StartingPrice+StartingPrice\times locationProximityWeight;$

10: Save OrderID if price is the highest so far;

11: end for

12: Sell to highest offer; $\triangleright$ Provided that minimum expectations
set beforehand are met

13: if no Buy orders then

14: Create Sell order

15: end if

16:else if $Action=BUY$ then

17: for $everySellorder$ do

18: $GetStartingPrice;$$\triangleright$ greenEnergyWeight has been factored in

19: $Price=StartingPrice+StartingPrice\times locationProximityWeight;$

20: Save OrderID if price is the lowest so far;$\triangleright$ may skip
orders concerning non-green energy

21: end for

22: Buy lowest offer; $\triangleright$ Provided that minimum expectations set
beforehand are met

23: if no Sell orders then

24: Create Buy order

25: end if

26:end if

The trading process is comprehensively outlined in 1, encompassing a series of
steps that ensure efficient electricity exchange. Initially, each node
determines whether it needs to buy or sell electricity. If a node possesses an
excess amount of electricity, it diligently searches for the most favorable
“buy” offer available at that particular moment. Once the search concludes,
the “sell” order is meticulously examined to ascertain if it meets any
predetermined minimum requirements established by the seller. Subsequently,
upon finding a “buy” order that satisfies these prerequisites, the transaction
is promptly executed. However, if no “buy” order meets the seller’s specified
requirements, a corresponding “sell” order is generated with the expectation
of being matched by an equally qualified “buy” order. The same procedure is
reversed when a node intends to purchase electricity. In this scenario, the
node strives to identify a matching “sell” order and, if unsuccessful, creates
a “buy” order accordingly.

###  5.2 Performance Evaluation of the Trading Mechanism

The experimental setup for the subsequent evaluation remains consistent with
the description provided in Section 4. Leveraging the pre-established trust
relationships, a series of experiments were conducted to showcase the intended
functionality of the RETINA energy trading system, enabling nodes to achieve
independence from traditional providers. These experiments highlight that
price fluctuations align with participants’ inclination to buy or sell
electricity, per the fundamental principle of supply and demand. To facilitate
this demonstration, a simulation environment was created, encompassing a
predetermined number of neighborhoods, participating nodes, and their
corresponding attributes: $(i)$ individual electricity reserves, $(ii)$
electricity reserve thresholds which when crossed the participant seeks to
either buy or sell electricity, and $(iii)$ electricity consumption and
production rate.

It is worth noting that to attain more realistic outcomes, randomness was
incorporated into the individual electricity reserves, consumption rates, and
production rates. This stochastic component was introduced to better simulate
real-world scenarios’ inherent variability and uncertainties. By including
this randomness, the experimental setup aimed to capture the dynamic nature of
electricity trading and accurately reflect the diverse characteristics and
behaviors of participating nodes.

Three distinct scenarios have been explored, each based on the initial
intentions of the participating nodes. These scenarios encompass:

1st Scenario: 75% Buyers, 25% Sellers

2nd Scenario: 50% Buyers, 50% Sellers

3rd Scenario: 25% Buyers, 75% Sellers

Table 2: Energy trading network configurations

| Network Configuration 1 | Network Configuration 2
---|---|---
Neighborhoods | 10 | 3
Nodes per Neighborhood | 30 | 100
Market Cycles | 30 | 30

For each scenario, two distinct network configurations were employed during
the simulation, denoted as Network Configuration 1 and Network Configuration
2. The “Market Cycle” concept was established to represent a timeframe within
which each network node engaged in electricity production, consumption, and
corresponding buying or selling activities based on their energy reserves.
Table 2 provides an overview of the network configurations utilized for the
simulation. In Network Configuration 1, the area was divided into ten
neighborhoods, each with ten nodes. Conversely, Network Configuration 2
maintained the same number of total network participants but redistributed the
nodes across a smaller number of neighborhoods. By comparing the electricity
price reactions in both configurations, the aim was to demonstrate the
feasibility and unimpeded interconnectivity between neighborhoods.
Furthermore, it was assumed that the provider offered incentives to encourage
the consumption of green energy, leading to the definition of specific weight
values as follows: $(i)$ greenEnergyWeight = 0.2 and $(ii)$ locationProximity
= 0.5.

In both Network Configuration 1 (Figure 10) and Network Configuration 2
(Figure 11), the expected price fluctuations are observed, aligning with the
principles of supply and demand. When the number of buyers exceeds that of
sellers, the price increases, while the opposite scenario leads to a decrease
in price. The introduction of randomness in the simulation results in a
realistic price graph that reflects the electricity needs of the network. In
Network Configuration 1, where a higher presence of buyers is combined with
the majority of buyers and sellers residing in different neighborhoods,
resulting in a weight of 0.5 factored into the final price calculation, the
price is driven higher compared to Network Configuration 2. The brokers
successfully execute their roles by considering the nodes’ requirements and
finding the most suitable Sell or Buy orders. Notably, the results demonstrate
that the entire grid is self-sustained, with none of the nodes relying on the
Utility for electricity.

Figure 10: kW price chart – Network configuration 1 Figure 11: kW price chart
– Network configuration 2

##  6 Security Analysis

The subsequent security analysis primarily identifies potential attack
scenarios that may arise due to the innovative characteristics inherent in the
described architecture. The aim is to assess the system’s vulnerability to
security threats and devise appropriate mitigation measures. By
comprehensively examining the security landscape, it becomes possible to
enhance the robustness and resilience of the architecture, ensuring the
protection of critical resources and maintaining the integrity of the overall
system.

###  6.1 DoS Attacks

The functionality of RETINA heavily relies on the empowered nodes,
particularly regarding blockchain operations. While the network operates in a
distributed manner without a single point of failure, a coordinated attack
targeting these specific nodes could potentially disrupt the entire network.
However, robust mitigation measures have been implemented, including
establishing trust relationships among entities independent of empowered
nodes. In the event of such an attack, the most trusted node(s) within the
affected neighborhood would assume an elevated role, temporarily replacing the
compromised empowered node. This ensures the continuity of network operations
and growth, as demonstrated in the performance evaluation, even in a worst-
case scenario. The system’s resilience safeguards against potential
disruptions and underscores the effectiveness of the implemented mechanisms in
addressing security concerns.

###  6.2 Energy Trading Privacy

The privacy of information stored on the ledgers is an inherent characteristic
of the permissioned blockchain employed by RETINA. This ensures that entities
not participating in the network cannot access the associated data. However,
it is important to acknowledge the possibility of a node being compromised and
maliciously exploited to leak information outside the smart grid ecosystem. If
such a scenario occurs, indicating a failure of the remote attestation
procedure, measures are in place to anonymize the stored information using the
Pk/Sk pairs possessed by each node through the utilization of TEE. This
ensures that external parties cannot obtain readable and usable information
unless they are part of the network. Specifically, while the provider can
match a node ID to a specific smart meter or empowered node, readable and
usable information remains inaccessible to external entities, preserving the
data’s privacy.

###  6.3 Attack of the Clones

Like the well-known $51\%$ attack and the Byzantine problem, the proof of
authority consensus mechanism can be vulnerable [26] if there is an
insufficient number of nodes available to validate transactions relative to
the network’s size. However, this vulnerability can be effectively mitigated
by ensuring an adequate number of empowered nodes within the network.
Additionally, including seemingly ordinary nodes that are prepared to assume
authoritative responsibilities in the event of a security incident or
compromise of an empowered node further strengthens the system’s resilience.
By maintaining a sufficient number of empowered nodes and establishing
contingency plans with backup nodes, the potential risks associated with the
proof of authority consensus mechanism can be effectively addressed,
bolstering the overall security and stability of the network.

###  6.4 Energy Trading Manipulation

The electricity offered within the energy trading mechanism can be regarded as
a tradable commodity, accompanied by various associated risks. One such risk
involves the potential for exploiting price differentials by purchasing
inexpensive electricity during the night and selling it at a higher price
during the day. However, several factors contribute to the unlikelihood of
such an attack materializing:

  * 1.

Continuous Production of New kW: Prosumers continuously generating new
electricity mitigates the probability of experiencing a shortage on the grid.
This ongoing production ensures a relatively stable supply, reducing the
feasibility of manipulating prices through artificial scarcity.

  * 2.

Price Adaptation: In response to an increase in demand, whether during the day
or night, the pricing mechanism within the energy trading system adapts
accordingly. This dynamic adjustment helps balance supply and demand, limiting
opportunities for price manipulation.

  * 3.

Optimized Broker Behavior: The broker component of the system is designed to
learn from the behavior of the energy trading mechanism, enabling it to make
informed decisions. By monitoring patterns and identifying nodes that
frequently require external assistance for electricity, the broker can
anticipate future needs and ensure fulfillment during periods of lower
electricity prices.

By considering these factors, the energy trading mechanism mitigates the risks
associated with opportunistic trading strategies and promotes a fair and
efficient marketplace for electricity exchange.

##  7 Critical Appraisal

In summary, RETINA presents a solution that addresses the challenges outlined
in Section 1, offering smart grids the means to overcome these obstacles and
unlock their full potential by incorporating an energy trading mechanism. This
achievement is made possible by strategically integrating several established
and proven technologies and concepts, including blockchain, PKI, and the WoT.
By combining these elements, RETINA establishes a robust foundation that
synergistically complements one another, providing a comprehensive solution
for the smart grid domain.

By implementing RETINA, a notable advancement towards achieving autonomy and
independence from centralized solutions within smart grid ecosystems is
realized. While a central authority, represented by the provider, establishes
policies and configures the network initially, once normal operations
commence, smart grids exhibit self-sovereign characteristics and can
autonomously perform fundamental functions. RETINA’s blockchain infrastructure
addresses the limitations often encountered in related literature that employs
similar DL concepts. This innovative solution minimizes operational costs and
optimizes the utilization of computational resources available within smart
meters, leading to enhanced efficiency and improved resource management. The
integration of RETINA thus marks a significant milestone in progressing
towards fully autonomous smart grid ecosystems.

The scalability is a critical aspect supporting the claim of RETINA’s ability
to enable fully decentralized smart grid ecosystems. The experiments
demonstrate that RETINA-based smart grids can maintain their functionality in
a decentralized manner, even with networks comprising at least 500 nodes.
Given the nature of smart grids, which involve the execution of multiple
applications such as the energy trading mechanism, constant and frequent
communication among nodes is inevitable. Consequently, communication packets
are transmitted within short intervals, resulting in an incremental
“incubation” time for the network. This inherent characteristic ensures that
RETINA can effectively handle the increasing communication demands as the
network expands, facilitating the seamless operation of various applications
within the smart grid ecosystem. The scalability of RETINA further strengthens
its viability and potential for large-scale deployment in real-world smart
grid scenarios.

Direct access to collectively produced green energy from smart grid
participants holds significant importance for prosumers, liberating them from
the limitations of their infrastructures and the provider’s capacity to supply
electricity. With the implementation of the energy trading mechanism,
participants gain access to a vast green energy market, enabling them to buy
and sell electricity directly. This arrangement offers substantial financial
benefits for all involved parties while contributing to environmental
sustainability. By facilitating direct transactions within the smart grid
ecosystem, RETINA empowers prosumers to actively participate in the green
energy market, fostering a more efficient and environmentally conscious energy
consumption landscape.

##  8 Related Work

The existing body of research on smart grid security is vast, with numerous
works exploring various aspects such as user and device authentication, data
privacy and confidentiality, and secure communication channels. To provide a
comprehensive understanding of the innovations proposed in this paper, the
related work is discussed in two distinct categories: $(i)$ security solutions
for smart grids and $(ii)$ security solutions specifically designed for energy
trading mechanisms. By examining the related work in these categories, this
paper aims to highlight the novel contributions of the proposed framework in
addressing the security challenges of both smart grids and energy trading
mechanisms. The discussion of previous research provides valuable insights
into the existing state of the art, enabling a clear understanding of the
advancements and innovations offered by the proposed solution.

###  8.1 Smart Grid Security

The following works focus on the authentication and privacy aspects provided
by blockchain technology in the context of IoT and smart grids, which are
vital for successfully implementing endeavors such as an energy trading
mechanism. Yakubov et al. [27] propose an authentication solution that
combines an x.509 certificates ecosystem with blockchain technology, covering
processes like issuance, validation, and revocation of certificates. However,
a drawback of this approach is that if the certificate authority loses access
to the blockchain and is excluded from the network, a new certificate
authority smart contract must be created, completely restructuring the
network’s certificates. In contrast, RETINA handles the exclusion of central
nodes differently, allowing operations to continue based on endorsements among
network nodes.

Wang et al. [28] present an anonymous authentication and key management scheme
for smart grids utilizing edge computing and blockchain technology.
Experimental results demonstrate its efficiency and speed. However, a single
point of failure is observed in their solution, where if an edge server goes
offline, the corresponding nodes’ connection to the blockchain network is
disrupted. This issue is not present in RETINA, as nodes are independently
connected to the blockchain.

Zhang et al. [29] design a decentralized access-control manager that utilizes
the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm for
participant authentication. The network’s security relies on the assumption
that malicious nodes will not reach a threshold defined by the PBFT’s security
requirements, which limits scalability. In contrast, RETINA employs remote
attestation based on TEE to exclude malicious nodes from the network rather
than tolerating them.

Finally, Bolgouras et al. [30] combine the PKI and WoT concepts into a hybrid
solution tailored for microgrids. While innovative and efficient in search
speed, this solution falls short compared to RETINA regarding nodes joining
and leaving operations. In their approach, when a node goes offline or rejoins
the network, a reconstruction of successor nodes where certificates are stored
is required, whereas, in RETINA, certificates remain on the DL without any
alterations.

By leveraging blockchain technology in RETINA, network security is enhanced
through the blockchain’s transparency, immutability, and accountability
properties. RETINA improves detection of malicious actions by auditing the DL
entries and renders a DHT obsolete for information logging purposes.

###  8.2 Energy trading

Park et al. [31] and Bosco et al. [32] propose energy trading schemes using
the Ethereum blockchain infrastructure. However, the high transaction fees
associated with the Ethereum network reduce the financial benefits for
potential adopters. In contrast, RETINA is built on the Hyperledger platform,
utilizing a PoA consensus algorithm, which enables transactions without fees.

Aitzhan et al. [33] present a decentralized energy trading system using
blockchain technology. The authors emphasize the requirement for multiple
signatures to execute a transaction. A transaction must be signed by a
predetermined number of participating entities in their scheme before being
submitted to the blockchain. In RETINA, entities form trust bonds and do not
need to sign numerous transactions constantly.

Regarding payments in energy trading, Aitzhan et al. [33] utilize the Bitcoin
system, which relies on the power-hungry Proof-of-Work (PoW) consensus
algorithm. This protocol is not suitable for resource-constrained IoT devices
like smart meters. Similarly, Li et al. [34] suggest an ecosystem where
prosumers can trade electricity using the blockchain-based medium of exchange,
NRGcoin, which also employs PoW. Although the consensus algorithm is executed
on aggregators with enhanced processing power, it still contradicts the
principle of energy efficiency.

Gai et al. [35] introduce a solution to ensure consumer-privacy regarding
trading habits and patterns on the blockchain. However, this solution relies
on a centralized exchange rather than a peer-to-peer bartering process, making
it susceptible to a single point of failure risk. All trading activities pass
through the Token Bank responsible for the transactions.

In contrast, RETINA addresses these challenges by utilizing a decentralized
architecture, low-cost transactions, and a PoA consensus algorithm, ensuring
energy efficiency, scalability, and resilience against single point of
failure.

##  9 Conclusions

Smart grids are experiencing rapid global adoption, but there is still
considerable room for improvement in terms of performance, security, and
efficacy. In this context, RETINA emerges as a groundbreaking solution that
addresses the diverse needs and requirements of modern smart grids. By
integrating the PKI/WoT architectures with blockchain technology, RETINA
establishes a resilient infrastructure that is immune to CA-oriented threats,
operating in a decentralized and distributed manner.

The scalability and resilience of RETINA were extensively validated through
simulations on a virtualized testbed environment consisting of 500 nodes. The
results demonstrate that RETINA outperforms the Web of Trust scheme,
significantly reducing the time required for new nodes to establish trust
relationships. Furthermore, even in the presence of compromised sections
within the grid, RETINA ensures uninterrupted network operations, showcasing
its robustness. Additionally, this paper presents a novel energy trading
scheme based on smart contracts, leveraging the established trust between
network nodes and adapting electricity prices based on factors such as
distance to prosumers and the chosen production method. This secure energy
trading mechanism plays a crucial role in unlocking the full potential of
renewable energy sources.

With its comprehensive capabilities, RETINA has the potential to set the
course for smart grids, unlocking their true potential and providing a solid
foundation for the implementation of intelligent programs with diverse
functionalities. As an ongoing research initiative, future work will apply the
trust management scheme to a realistic testbed involving an actual smart grid
deployment. Furthermore, RETINA will be enhanced with additional applications
beyond energy trading, further cementing its position as a pioneering
solution.

In summary, RETINA represents a significant advancement in revolutionizing
smart grids, offering a comprehensive solution that addresses their current
limitations. Its innovative design and proven performance make it a milestone
achievement, propelling the industry towards a future where intelligent
programs and cutting-edge functionalities find abundant opportunities for
application.

## Acknowledgements

The authors would like to thank Dr. Apostolos Zarras for his valuable input in
improving the readability and quality of this paper. His expertise and
suggestions have greatly enhanced the overall clarity and flow of the
manuscript. We are grateful for his valuable contributions and support
throughout this research project.

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