**3. Proposed algorithm**

*Digital Forensic Science*

which is defined as:

distributed uniformly.

lowing way:

used for encryption.

in [0, 1]:

Another chaos map is Tent Map. It iterates a point *x*0 and gives a sequence *xi*

ì < ïï = = í

m

where μ is a positive real constant. Varian of Tent Map is Skew Tent Map [8]

1

ï = = í - ï < £ ïî -

*i*

m

*x*

*i*

m

1

where *μ* is system parameter and *x*0 is initial condition of map. When a Skew Tent Map is iterated from *x*0 value, it produces a sequence in the interval [0, 1] and

> *x fx i i* +1 = m

*y gy i i* +1 = m

where *μ* is system parameter and is same for both maps. The CCCBG generated a sequence of random bits by comparing the outputs of the maps in the fol-

( ) 1 1

Based on several tests performed by Narendra et al., the CCCBG successfully passes all the randomness tests [10], therefore the random binary sequences can be

ì < = í ³ î

0 , , 1 ,

1 1

+ +

*i i*

+ +

*i i x y hx y x y* (6)

1 1

+ +

*i i*

Narendra et al. in [10] proposed a random bit generator based on two Skew Tent Maps. The generator is abbreviated as CCCBG (Cross-Coupled Chaotic random Bit Generator). In the CCCBG, random bit stream is generated by comparing outputs of the couple maps. If *fμ*(*xi*) and *gμ*(*yi*) are two Skew Tent Maps and are given as:

m

1 , 2

1 ,

*i i*

*x x*

*i i*

*x x*

,0

m

ì £ < ï

, 1

*x*

*i*

*x*

ï - ³ ïî

1

(2)

(3)

2

m

( ) (4)

( ) (5)

( ) ( ) 1

+

+

*i i*

m

1 ( )

m

*x fx x*

*i i*

*x fx*

**40**

**Figure 1.**

*A random image generated by using the CCCBG.*

This section will explain the proposed fragile video watermarking on spatial domain based on the chaotic map. The watermark is a binary image. To detect manipulation in the video frames until pixel level, the watermark must have the same size as the video frame size. Therefore, if watermark size is less than video frame size, the watermark need to be replicated by duplicating it a number of times in order to produce a new watermark that has the same size with the host video frame size. **Figure 2** shows example of replication. The original watermark "ASEAN logo" has a size of 200 × 194 pixels, whereas the video frames have a size of 480 × 854 pixels. This original watermark must be duplicated a number of times so that produce a replicated watermark that has size 480 × 854.

Next, to increase security, before embedding, the replicated watermark is encrypted by XOR-ing it with a random image. A random image is generated by iterating CCCBG a number of *mn* times where *m* and *n* are frame sizes (**Figure 1**). The replicated watermark is encrypted with the random image by using XOR operation to produce an encrypted watermark (**Figure 3**). Next, we embed the encrypted watermark into the host video.

We design a simple, but secure, fragile video watermarking based on chaos. The fragile video watermarking algorithm consists of two processes: embedding algorithm and extraction algorithm, each will be described below.

### **3.1 Watermark embedding algorithm**

There are two scenarios for embedding the watermark into a digital video. The first scenario is embedding each frame of the video with the same watermark. The second scenario is embedding each frame of the video with the different watermark. The second scenario is not practical because the video owner have to provide the watermark of as many frames. Actually, the watermarks can be generated from the video itself (i.e., internal watermarks), we generate the watermark for each video frame that

**Figure 2.** *Left: the original watermark; right: the replicated watermark.*

**Figure 3.** *Left: the replicated watermark. Right: the encrypted watermark.*

depend on the frame content itself. However, the resulting watermark is meaningless and cannot be perceived visually. We want the watermark to be meaningful and can be perceived visually. Therefore, we choose the watermark is a meaningful binary image and, for practical reason, the same watermark is embedded to each video frame.

Now, we can describe the watermark embedding algorithm into the digital video in more detail as follows:

**Input**: a host video file (*v*), a watermark file (*w*), and CCCBG's parameter and initial conditions (*μ*, *x*0, *y*0).

**Output**: a watermarked video (*v*').

Step 1: Read the frames of video *v*, the watermark *w*, and CCCBG's parameter and initial conditions (*μ*, *x*0, and *y*0). If the video has an audio, then separate the audio.

Step 2: If size(*w*) < size(video frame of *v*), copy the single watermark to produce a replicated watermark *w*' which has the same size with the host video frames.

Step 3: Iterate CCCBG *mn* times to produce a random image *r*.

Step 4: Encrypt *w*' by XOR-ing it with *r* as follows:

$$
\omega \nu \prime = \omega \prime \oplus r \tag{7}
$$

**43**

region in a frame.

**4. Experiment and results**

*Application of Chaos-Based Fragile Watermarking to Authenticate Digital Video*

Step 6: If the original video has audio, merge it to the watermarked frames to

**Figure 4** shows stages in the watermark embedding algorithm. The watermark is embedded into each frames of video. If the video has audio, the audio has not been changed. After embedding of the watermark, audio is merged back into the video.

Watermark extraction from the video is performed to prove video authentication. Only the video owner can do it, because the owner has the original watermark. The original watermark is required to compare it with the extracted watermark. If the extracted watermark is the same as the original watermark (can be observed visually), then we decide that the video is authentic, otherwise the video has been altered, tampered, or manipulated. The original watermark is also required to localize the tampered region in a frame. Watermark extraction can be performed on all

Now, we can describe the watermark extraction algorithm from the digital video

**Input**: a watermarked video file (*v*'), an original watermark file (*w*), and

Step 1: Read the frames of video *v*', watermark *w*, and CCCBG's parameter and

Step 2: If size(*w*) < size(video frame of *v*), copy the single watermark to produce

Step 4: For each frame, extract all of the least significant bit (LSB) of pixels. This

*w*"' = *w*" ⊕ *r.* (8)

Step 5: Compare *w*"' with *w*'. If *w*"' = *w*', we conclude that the integrity of video

Step 6: To localize tampered region, subtract *w*' to *w*"'. If a pixel is not changed,

Step 7: Identify pixels in the watermarked framed in position where the subtrac-

**Figure 5(a)** shows stages in the watermark extraction algorithm. The watermark is extracted from each frame of video and then compares the extracted watermark to the original watermark. The decision is binary (1 or 0), 0 means the watermarked

We have implemented the proposed algorithm to be a computer program. Next we test the algorithm on a sample video to determine authentication of the video. The

video has not changed (authentic), 1 means the watermarked video has been manipulated, altered, or tampered. **Figure 5(b)** shows how to localize tampered

**Output**: an extracted watermark, location of tampered frame (if any).

a replicated watermark *w*' which has the same size with the host video frames.

Step 3: Iterating CCCBG *mn* times to produce a random image *r*.

Step 4: Decrypt the watermark *w*" by XOR-ing it with *r* as:

tion above yields 1. Those are pixels that have been manipulated.

*DOI: http://dx.doi.org/10.5772/intechopen.93151*

**3.2 Watermark extraction algorithm**

video frames or only on certain frames.

CCCBG's parameter and initial conditions (*μ*, *x*0, and *y*0).

in more detail as follows:

initial conditions (*μ*, *x*0 and *y*0).

step yields an extracted watermark *w*".

is authenticated. If not, go to step 6 and 7.

the subtraction yields 0, else the subtraction yields 1.

produce a watermarked video.

Step 5: Embed the encrypted watermark, *w*", into each frame of the video by manipulating the least significant bit (LSB) of pixels. If the frame has R, G, and B component, then it performs embedding to each component.

**Figure 4.** *Watermark embedding algorithm.*

Step 6: If the original video has audio, merge it to the watermarked frames to produce a watermarked video.

**Figure 4** shows stages in the watermark embedding algorithm. The watermark is embedded into each frames of video. If the video has audio, the audio has not been changed. After embedding of the watermark, audio is merged back into the video.

### **3.2 Watermark extraction algorithm**

*Digital Forensic Science*

in more detail as follows:

initial conditions (*μ*, *x*0, *y*0).

the audio.

**Figure 3.**

**Output**: a watermarked video (*v*').

*Left: the replicated watermark. Right: the encrypted watermark.*

depend on the frame content itself. However, the resulting watermark is meaningless and cannot be perceived visually. We want the watermark to be meaningful and can be perceived visually. Therefore, we choose the watermark is a meaningful binary image and, for practical reason, the same watermark is embedded to each video frame.

Now, we can describe the watermark embedding algorithm into the digital video

**Input**: a host video file (*v*), a watermark file (*w*), and CCCBG's parameter and

Step 1: Read the frames of video *v*, the watermark *w*, and CCCBG's parameter

Step 2: If size(*w*) < size(video frame of *v*), copy the single watermark to produce

*wwr* " ' = Å (7)

and initial conditions (*μ*, *x*0, and *y*0). If the video has an audio, then separate

a replicated watermark *w*' which has the same size with the host video frames.

Step 5: Embed the encrypted watermark, *w*", into each frame of the video by manipulating the least significant bit (LSB) of pixels. If the frame has R, G, and B

Step 3: Iterate CCCBG *mn* times to produce a random image *r*.

Step 4: Encrypt *w*' by XOR-ing it with *r* as follows:

component, then it performs embedding to each component.

**42**

**Figure 4.**

*Watermark embedding algorithm.*

Watermark extraction from the video is performed to prove video authentication. Only the video owner can do it, because the owner has the original watermark. The original watermark is required to compare it with the extracted watermark. If the extracted watermark is the same as the original watermark (can be observed visually), then we decide that the video is authentic, otherwise the video has been altered, tampered, or manipulated. The original watermark is also required to localize the tampered region in a frame. Watermark extraction can be performed on all video frames or only on certain frames.

Now, we can describe the watermark extraction algorithm from the digital video in more detail as follows:

**Input**: a watermarked video file (*v*'), an original watermark file (*w*), and CCCBG's parameter and initial conditions (*μ*, *x*0, and *y*0).

**Output**: an extracted watermark, location of tampered frame (if any).

Step 1: Read the frames of video *v*', watermark *w*, and CCCBG's parameter and initial conditions (*μ*, *x*0 and *y*0).

Step 2: If size(*w*) < size(video frame of *v*), copy the single watermark to produce a replicated watermark *w*' which has the same size with the host video frames.

Step 3: Iterating CCCBG *mn* times to produce a random image *r*.

Step 4: For each frame, extract all of the least significant bit (LSB) of pixels. This step yields an extracted watermark *w*".

Step 4: Decrypt the watermark *w*" by XOR-ing it with *r* as:

$$
\mathfrak{w}^{\prime\prime\prime} = \mathfrak{w}^{\prime\prime} \oplus \mathfrak{r}.\tag{8}
$$

Step 5: Compare *w*"' with *w*'. If *w*"' = *w*', we conclude that the integrity of video is authenticated. If not, go to step 6 and 7.

Step 6: To localize tampered region, subtract *w*' to *w*"'. If a pixel is not changed, the subtraction yields 0, else the subtraction yields 1.

Step 7: Identify pixels in the watermarked framed in position where the subtraction above yields 1. Those are pixels that have been manipulated.

**Figure 5(a)** shows stages in the watermark extraction algorithm. The watermark is extracted from each frame of video and then compares the extracted watermark to the original watermark. The decision is binary (1 or 0), 0 means the watermarked video has not changed (authentic), 1 means the watermarked video has been manipulated, altered, or tampered. **Figure 5(b)** shows how to localize tampered region in a frame.

## **4. Experiment and results**

We have implemented the proposed algorithm to be a computer program. Next we test the algorithm on a sample video to determine authentication of the video. The

**Figure 5.**

*(a) Watermark extraction algorithm and (b) localize tampered region.*

sample video was a video clip which has 394 frames and long 16 seconds, each frame has a size 480 × 854 (**Figure 6a**). This video contains audio inside. **Figure 6b** and **c** show two frames of the video (frame 1 and frame 175).

The watermark to be embedded into the host video is "ASEAN logo" as shown in **Figure 3** (after replicated). In these experiments below, we used parameters of CCCBG as follows: *μ* = 0.48999, initial conditions *x*0 = 0.5006841, and *y*0 = 0.538167586. The two initial conditions serve as the secret keys. These keys were used in both watermark embedding algorithm and extraction algorithm.

This algorithm can only be used to test the authentication of digital videos that have been spatially manipulated. Spatial manipulation such as changing the contrast of the image, adding noise, changing the size of the frame, copy and paste an object into the frame, and others. The algorithm cannot temporarily detect video manipulation, for example, by removing one or more frames.

In the section below, we divide experiments into two cases: (i) no attack case and (ii) tamper detection test, each will be described below.

### **4.1 No-attack case**

If the watermarked video is not manipulated, we categorized it as no attack case. To prove the authentication of the video, we extracted all watermarks from each video frame. All watermarks should be the same as the original watermark. **Figure 7** shows the extracted watermarks but only from frame number 1 and frame number 283.

Visually, there are no damages in the extracted watermarks. When we compare the extracted watermark to the original watermark by subtracting them, we get

**45**

watermark.

**Figure 7.**

**Figure 6.**

*The watermarked frames and the extracted watermarks.*

*(a) A host video to be watermarked, (b) frame 1, and (c) frame 175.*

*Application of Chaos-Based Fragile Watermarking to Authenticate Digital Video*

the difference is a black image (all of pixels are 0). Therefore, we conclude no tampering performed to the watermarked video. In this algorithm, parameter and initial condition of CCCBG behave as secret keys. Embedding and extraction of the watermark could be done by the authorized party only. If the receiver did not have the same keys, then the extracted watermark is not the same as the original

*DOI: http://dx.doi.org/10.5772/intechopen.93151*

*Application of Chaos-Based Fragile Watermarking to Authenticate Digital Video DOI: http://dx.doi.org/10.5772/intechopen.93151*

**Figure 6.**

*Digital Forensic Science*

sample video was a video clip which has 394 frames and long 16 seconds, each frame has a size 480 × 854 (**Figure 6a**). This video contains audio inside. **Figure 6b** and **c**

The watermark to be embedded into the host video is "ASEAN logo" as shown

This algorithm can only be used to test the authentication of digital videos that have been spatially manipulated. Spatial manipulation such as changing the contrast of the image, adding noise, changing the size of the frame, copy and paste an object into the frame, and others. The algorithm cannot temporarily detect video

In the section below, we divide experiments into two cases: (i) no attack case and

If the watermarked video is not manipulated, we categorized it as no attack case. To prove the authentication of the video, we extracted all watermarks from each video frame. All watermarks should be the same as the original watermark. **Figure 7** shows the extracted watermarks but only from frame number 1 and frame number 283.

Visually, there are no damages in the extracted watermarks. When we compare the extracted watermark to the original watermark by subtracting them, we get

in **Figure 3** (after replicated). In these experiments below, we used parameters of CCCBG as follows: *μ* = 0.48999, initial conditions *x*0 = 0.5006841, and *y*0 = 0.538167586. The two initial conditions serve as the secret keys. These keys were used in both watermark embedding algorithm and extraction algorithm.

show two frames of the video (frame 1 and frame 175).

*(a) Watermark extraction algorithm and (b) localize tampered region.*

manipulation, for example, by removing one or more frames.

(ii) tamper detection test, each will be described below.

**44**

**4.1 No-attack case**

**Figure 5.**

*(a) A host video to be watermarked, (b) frame 1, and (c) frame 175.*

**Figure 7.** *The watermarked frames and the extracted watermarks.*

the difference is a black image (all of pixels are 0). Therefore, we conclude no tampering performed to the watermarked video. In this algorithm, parameter and initial condition of CCCBG behave as secret keys. Embedding and extraction of the watermark could be done by the authorized party only. If the receiver did not have the same keys, then the extracted watermark is not the same as the original watermark.

**Figure 8.** *The watermarked frames and the extracted (wrong) watermarks.*


*2.4. Viral Loads in Bloods*

Primary viremia of TD/96 strain was first detected in both co-infected\_P1 pigs and co-infected\_P2 pigs at 2 dpi, and in co-infected with Ab pigs at 4 dpi, earlier than that of 94.4 strain, which was first detected in co-infected\_P1 pigs at 4 dpi and in both co-infected\_P2 pigs and co-infected with Ab pigs at 6 dpi (Figures 2A and 3A, Table 1). The viral loads of the TD/96 strain were always significantly higher than those of the 94.4 strain (*p* < 0.05) (Figures 2A and 3A) in all the co-infected pigs. The viral loads of the TD/96 strain were on average 1.89, 2.93, and 1.51 log higher than that of the 94.4 strain at all dpi in co-infected\_P1 pigs, co-infected\_P2 pigs and co-infected with Ab pigs, respectively. Comparing the three groups, the co-infected\_P2 pigs had the highest lead of TD/96 at all dpi; the viral loads were above 3 log higher than that of the 94.4 strain at 4 and 6 dpi. The highest lead of TD/96 was observed at 4 dpi, when it was on average 3.96 log higher than that of the 94.4 strain. No lead of TD/96 was above 3 log in co-infected\_P1 pigs or co-infected with Ab pigs.

**Figure 2.** Comparison of viral loads of co-infected\_P1 (Group 1) and co-infected\_P2 pigs (Group 2). Viral loads in (**A**) blood, (**B**) oral swabs, (**C**) fecal swabs, and (**D**) organs of co-infected\_P1 and co-infected\_P2 pigs were quantified by reverse transcription multiplex real-time polymerase chain reaction. The data represent the mean and standard deviation from three pigs. Values with different superscript letters, a–d, among the four groups of samples at the same dpi (**A–C**) or the same organ (**D**) indicate a statistically significant difference (*p* < 0.05) from each other. The superscript letter "a" indicates the highest viral load and "d" indicates the lowest viral load among the compared groups, while "ab" indicates a viral load in between categories "a" and "b". No significant differences exist between values containing the same letter. The absence of a superscript letter indicates no statistical analysis due to only one sample of a group or only one group within the same dpi.

**Figure 3.** Comparison of viral loads of co-infected\_P1 (Group 1) and co-infected with Ab pigs (Group 3). Viral loads in (**A**) blood, (**B**) oral swabs, (**C**) fecal swabs, and (**D**) organs of co-infected\_P1 and co-infected with Ab pigs were quantified by reverse transcription multiplex real-time polymerase chain reaction. The data represent the mean and standard deviation from three pigs. Values with different superscript letters, a–d, among the four groups of samples at the same dpi (**A–C**) or the same organ (**D**) indicate a statistically significant difference (*p* < 0.05) from each other. The superscript letter "a" indicates the highest viral load and "d" indicates the lowest viral load among the compared groups, while "ab" indicates a viral load in between categories "a" and "b". No significant differences exist between values containing the same letter. The absence of a superscript letter labeled indicates no statistical analysis due to only one sample of a group or only one group within the same dpi.

#### *2.5. Viral Loads in Secretions and Excretions*

In co-infected\_P2 pigs, the TD/96 strain was first detected in oral swabs and fecal swabs at 4 to 6 dpi, whereas in co-infected\_P1 pigs and co-infected with Ab pigs, the TD/96 strain first presented at 6 to 8 dpi (Table 1). The 94.4 strain was first detected in oral swabs and fecal swabs at 8 to 10 dpi in all co-infected pigs, except one co-infected\_P2 pig that died at 9 dpi, in which the virus was not detected (Table 1).

In oral swabs, the viral loads of the TD/96 strain were always significantly higher than those of the 94.4 strain in all the co-infected pigs (*p* < 0.05) (Figures 2B and 3B), with only one exception at 10 dpi of co-infected with Ab pigs. The viral loads of the TD/96 strain were on average 1.88, 3.08 and 1.59 log higher than that of the 94.4 strain at all dpi in co-infected\_P1 pigs, co-infected\_P2 pigs and co-infected with Ab pigs, respectively. Comparing the three groups, the co-infected\_P2 pigs had the highest lead of TD/96 at all dpi, in which the viral loads were above 3 log higher than that of the 94.4 strain at 6 and 8 dpi. The highest lead of TD/96 was observed at 6 dpi, when it was on average 4.74 log higher than that of the 94.4 strain. No lead of TD/96 was above 3 log in co-infected\_P1 pigs or co-infected with Ab pigs.

In fecal swabs, the viral loads of the TD/96 strain were always significantly higher than those of the 94.4 strain in all co-infected pigs (*p* < 0.05) (Figures 2C and 3C), with only one exception at 8 dpi of co-infected\_P2. The viral loads of the TD/96 strain were on average 2.49, 2.7 and 1.84 log higher than that of the 94.4 strain at all dpi in co-infected\_P1 pigs, co-infected\_P2 pigs and co-infected with Ab pigs, respectively. Comparing the three groups, the co-infected\_P2 pigs had the highest lead of TD/96 at all dpi; the highest lead of TD/96, with on average 3.45 log higher than that of the 94.4 strain, was observed at 6 dpi. No lead of TD/96 was above 3 log in co-infected\_P1 pigs or co-infected with Ab pigs.

#### *2.6. Viral Loads in Visceral Organs*

The viral loads of the TD/96 strain were consistently significantly higher than those of the 94.4 strain in most tested organs (*p* < 0.05) (Figures 2D and 3D) in all pigs. The viral loads of the TD/96 strain were on average 2.39, 3.00, and 2.09 log higher than those of the 94.4 strain in co-infected\_P1 pigs, co-infected\_P2 pigs, and co-infected with Ab pigs, respectively. Comparing the three groups, the co-infected\_P2 pigs had the highest lead of TD/96 in most tested organs; the viral loads were above 2.5 log higher than that of the 94.4 strain. The highest lead of TD/96 was observed in lymph nodes, where it was on average 3.33 log higher than that of the 94.4 strain.

#### **3. Discussion**

The shift in CSFV populations in the field, from genotypes 1 and 3 to genotype 2, was observed worldwide [8–12]. However, the mechanisms responsible for the shift remain unclear. A previous study hypothesized that genotype 2 had higher genetic diversity than genotypes 1 and 3 did, which might explain why it is the most prevalent endemic situation [19]. Three hypotheses were proposed: First, virus strains of genotype 2.1 may have higher replication efficiency than the genotype 3.4 strains in pigs; second, the strains of genotype 2.1 may have higher affinity and competitiveness to cellular receptors than those of genotype 3.4; and third, the strains of genotype 2.1 may have better ability than those of genotype 3.4 to escape from antibody neutralization induced by the attenuated lapinized vaccine strain LPC of genotype 1.1, which has been used to protect pigs against the 3.4 strains since the 1950s in Taiwan [12]. To test the first two hypotheses, Huang et al. [18] allowed two viruses belonging to genotypes 2.1 and 3.4, respectively, to compete in vivo and in vitro, and the results revealed that the virus of genotype 2.1 replicated more efficiently than that of genotype 3.4. To further explore and to simulate the field situation, this study analyzed the competitions of the viruses of the two genotypes in co-infected pigs for two passages without neutralizing antibodies (Groups 1 and 2). Moreover, we also examined the dynamics of virus replication and disease development of the infected pigs in the presence of maternally derived neutralizing antibodies induced by LPC vaccine (Group 3). To the best of our knowledge, this study is the first attempt to test the competitions of CSFV in this way.

The new CSFV strain of genotype 2.1 has higher replication efficiency than the historical genotype 3.4 strain in pigs. Indeed, when given equal opportunity to compete in the same animal for the first passage of competition, the genotype 2.1 CSFV (represented by TD/96) had 2.43 log (8.3–5.87) higher TCID50 titer over that of genotype 3.4 (represented by 94.4) in the blood (Group 2 inoculum, Table 1). This advantage of TD/96 in blood was also amply supported by quantifications of viral loads using quantitative reverse transcription multiplex real-time polymerase chain reaction (RT-MRT-PCR) (Table 2). Under various dual infection conditions with or without the presence of maternal antibodies, the TD/96 strain had consistently 1.51−3.08 log higher loads than those of 94.4. The 2.43 log TCID50 replication advantage of TD/96 in the first passage of competition in an animal body falls within the range of 1.51–3.08 log, as estimated by RT-MRT-PCR. Given a second passage of competition, the lead of TD/96 was widened further. The TD/96 strain was first detected in oral swabs and fecal swabs of co-infected\_P2 pigs 2–4 days earlier than in those of co-infected\_P1 pigs. On the other hand, the 94.4 strain was first detected in viremia of co-infected\_P2 pigs 2 days later than in those of co-infected\_P1 pigs, despite the two groups having been inoculated with similar amounts of the 94.4 strain (106 TCID50/mL in co-infected\_P1 pigs and 105.87 TCID50/mL in co-infected\_P2 pigs). The results revealed that when the viruses of genotype 2.1 are dominant in the field, the viruses replicate more efficiently and shed earlier than the viruses of genotype 3.4 do. Therefore, the genotype of CSFV in the pig population shifted from genotype 3.4 to 2.1. Given further passages of dual infection in pigs, the competition edge of genotype 2.1 would likely lead to the disappearance of genotype 3.4 in pigs.

Colostrum maternal antibodies offer partial protection for dually infected pigs, despite the genotype difference of the LPC vaccine virus (of genotype 1.1) from those of genotype 2.1 and 3.4 of dually infected viruses (Group 3). The TD/96 and 94.4 strains were first detected in the blood of co-infected with Ab pigs 2 days later than in co-infected\_P1 pigs, although pigs in these two groups were inoculated with the same amounts of the TD/96 and 94.4 strains. The maternal antibodies protection was ineffective when the genotypic heterologous neutralizing titer dropped to below 1:4 during dpi 8−14 (Table 3), for febrile reactions were observed after 10 dpi (Figure 1). This finding suggests that the protection offered by the maternal antibodies is not limited to the initial engagement to neutralize incoming virus but also allows for the host to launch immune responses before the system is overwhelmed.

Antigenic variations among various genotypes of CSFVs certainly render the currently available vaccines more effective in neutralizing historical viruses, while allowing the newly invading virus to escape. This hypothesis has been amply addressed in several previous studies [20–23]. The neutralizing antibodies of co-infected with Ab pigs against the LPC/AHRI strain were higher than those against the TD/96 strain and the 94.4 strain. However, there was no significant difference between the neutralizing antibodies against the TD/96 strain and those against the 94.4 strain. This evidence supported previous studies that antibodies induced by live virus neutralize genotypically homologous strains better than heterologous strains [17,24,25]. In co-infected with Ab pigs, similarly to Group 1, the TD/96 strain was shed by infected pigs earlier than the 94.4 strain was. In addition, the viral loads of the TD/96 strain were significantly higher than those of the 94.4 strain. The results indicated that the presence of maternally derived antibodies induced by modified live virus of genotype 1.1 might not influence the competition between viruses of genotypes 2.1 and 3.4. Previous study demonstrated that the LPC vaccine could offer pigs protection from challenges of field viruses of genotypes 2.1 and 3.4 [26]. This study revealed that when pigs or piglets infected by CSFV field viruses of genotypes 2.1 and 3.4 were vaccinated, the vaccine's efficacy was interfered with, and also that when the maternally derived antibodies declined in piglets before vaccination, the pigs produced lower neutralizing antibodies and had delayed clinical signs. However, the CSFVs were detected in those infected pigs, in which the genotype 2.1 viruses were released earlier and replicated more efficiently than did genotype 3.4 viruses. These results may suggest that the newly invading strains dominated in the field under vaccination.

Contact infection may present another aspect of virus competition. To investigate how the competition occurs between viruses of genotypes 2.1 and 3.4, in this study we employed the intramuscular route for the co-infection. This route can ensure that both viruses enter the hosts with the same amount of virus simultaneously to allow comparison of their replication efficiency and pathogenicity. However, when the virus is introduced through natural routes, the influencing factors could be more numerous and much complicated. To further explore the natural situations and to evaluate the possible effect of the superinfection exclusion phenomenon of CSFV [27] in the field in terms of the competence of these two genotypes, cohabitation infection with 2.1 virus infected pigs and 3.4 virus infected pigs is warranted.

In conclusion, examining the competition of the historical and newly invading genotypes of CSFV in co-infected pigs with different virus populations and with maternally derived neutralizing antibodies revealed that the new CSFV genotype 2.1 replicates more efficiently, at 1.51–3.08 log higher than that of the historical genotype 3.4. The maternally derived antibodies provide partial protection to both wild type CSFVs and correlate with lower clinical scores, febrile reaction, and animal mortality. In the presence of maternal antibodies, pigs could be infected by both wild type CSFVs, with the genotype 2.1 dominating. These results could further our understanding of the prevalence of genotype 2 in the field, which is widely observed in Asia and Europe. This is the first time that the higher replication capacity of genotype 2.1 than that of genotype 3.4 has been demonstrated in vivo with this design.

#### **4. Materials and Methods**

#### *4.1. Cells and Viruses*

Porcine kidney-15 (PK-15) cells were maintained in minimum essential medium supplemented with 10% fetal bovine serum and incubated at 37 ◦C in 5% CO2. The three CSFV strains used in this study, comprised the two representative CSFV strains TD/96 and 94.4 and an attenuated lapinized vaccine strain LPC/AHRI, were propagated in the PK-15 cells [3,12,13].

#### *4.2. mAbs Specific for CSFV*

Three mAbs against CSFVs were used in this study. The mAbs T6 and L71 were produced by the Animal Health Research Institute, Taiwan, and the mAb WH303 by the Animal and Plant Health Agency, the United Kingdom. The mAb T6 recognizes the TD/96 strain of genotype 2.1 but not the 94.4 strain of genotype 3.4. In contrast, the mAb L71 recognizes the 94.4 strain but not the TD/96 strain [18]. The mAb WH303 reacts with most CSFV strains tested [28], including the three strains used in this study.

#### *4.3. Experimental Infections*

Six 4-week-old specific pathogen-free (SPF) pigs were randomly separated into two groups of three pigs: Groups 1 and 2 (Table 1). Pigs in Group 1 (co-infected\_P1) were inoculated intramuscularly with 1 mL of the TD/96 strain and 1 mL of the 94.4 strain simultaneously, each at a virus amount of 106 TCID50/mL, to ensure that both strains could enter the hosts simultaneously. The concept of the Group 1 co-infection experiment design was similar to that described in Group 3 of Huang et al. [18] and was repeated here, in separate pigs, for comparison with Groups 2 and 3 (see below). Pigs in Group 2 (co-infected\_P2) were inoculated intramuscularly with 1 mL of whole blood taken from a pig of Group 1 at 12 dpi. This inoculum contained TD/96 108.3 TCID50 and 94.4 105.87 TCID50 as titrated later (Table 1). Group 3 (co-infected with Ab) included three 4-week-old pigs born from a sow vaccinated with LPC vaccine, in which the maternal antibody response was in decline. These animals were chosen in order to examine the effect of antibody drop on co-infection. These pigs were inoculated intramuscularly with 1 mL of the TD/96 strain and 1 mL of the 94.4 strain simultaneously, as in Group 1, at 106 TCID50/mL. The three groups were housed separately in three negative air-pressure isolation units. For animal welfare reasons, pigs were euthanized when they were moribund and unable to stand up. All surviving pigs were euthanized at 14 dpi, the end of the experimental period. This animal experiment was approved by the Institutional Animal Care and Use Committee of the Animal Health Research Institute (Approval number A02040).

## *4.4. Clinical Signs, Body Temperature, and Sampling Procedures*

Rectal temperature was recorded daily during the experimental period. Fever was defined as a temperature higher than 40 ◦C. For evaluation of clinical signs, the ten parameters described by Mittelholzer et al. [29] were scored from 0 to 3 to represent normal to severe CSF symptoms. The scores of each pig were summed into a total score for each day. Blood, oral swabs, and fecal swabs were collected prior to inoculation at 0 dpi and then at 2-day intervals post infection. Swabs were weighed before and after sampling to normalize the viral loads. Each swab was immersed in 2 mL of phosphate buffered saline (PBS) and centrifuged at 3,000 × *g* for 10 min, and the harvested supernatant was stored at −70 ◦C. Necropsies were performed after euthanasia or death, and tissue samples of tonsil, submandibular and mesenteric lymph nodes, heart muscle, lung, liver, spleen, kidney, bladder, and cerebrum were collected from all pigs.

#### *4.5. Virus Titration*

Ten-fold serial diluted blood (inoculum of Group 2) at 12 dpi from a pig of co-infected\_P1 was added into eight wells each of 96-well plates duplicated and seeded with PK-15 cells. Whether the cells were infected was observed using indirect fluorescent assay (IFA) at 72 hours post infection (hpi). The mAbs T6 and L71 were used for virus titration. One 96-well plate was stained with mAb T6, which recognizes the TD/96 strain but not the 94.4 strain; the other 96-well plate was stained with mAb L71, which recognizes the 94.4 strain but not the TD/96 strain [18]. Virus titers were calculated as TCID50 using the Reed-Muench method [30].