 for a given inter-arrival time range. Gianvecchio and Wang showed that covert timing channels can be detected with high accuracy by analyzing the entropy of inter-arrival times [Gianvecchio and Wang 2007].
While statistical approaches have been effective primarily against channels based on the Inter-arrival Time pattern and the Random Value pattern, their application to all other patterns is thinkable, since the use of all covert channels leads to changes of statistical value distributions.
6.1.4. Machine Learning (ML). Covert channels can be detected using supervised ML approaches where some statistical features are used to characterize covert channels and normal traffic. Classifier models are then trained based on provided examples of features of covert channels and normal traffic. Sohn et al. demonstrated that simple covert channels encoded in the IP ID or TCP ISN field can be discovered with high accuracy by Support Vector Machines (SVMs) [Sohn et al. 2003]. Tumoian et al. showed that a neural network can detect Rutkowska's TCP ISN covert channel [Rutkowska 2004] with high accuracy [Tumoian and Anikeev 2005] (both Random Value pattern). Zander et al. demonstrated that inter-packet timing channels can be detected by C4.5 decision trees trained on several features [Zander et al. 2011] (Inter-arrival Time pattern). Wendzel and Zander showed that C4.5 decision trees also detect simple protocol switching channels (Value Modulation pattern) with high accuracy [Wendzel and Zander 2012]. Besides the mentioned patterns, the application of ML to detect all other patterns appears possible. 6.1.5. Applicability of Countermeasures. Tab. III summarizes our findings on the applicability of the discussed countermeasures in the context of covert channel patterns.
We did not only take existing applications of countermeasures but also potential applications into account, since no pattern-specific implementations are available yet. In general, the prevention of covert channels is always feasible if all traffic is blocked but such approaches are not applicable in practice or demand a high-quality covert channel detection. Therefore, Tab. III does not cover techniques which block the entire traffic.

Illustration: Traffic Normalization
Although traffic normalization was never discussed in the context of covert channel patterns, the existing normalizers already have pattern-oriented capabilities. As dozens of normalization techniques exist, we will discuss only selected ones to show that pattern-oriented countermeasures are feasible. For instance, existing normalizers can replace the TTL of IPv4 packets with a fixed value to eliminate covert channels. Traffic normalizers can apply the same technique to counter covert channels in the IPv6 hop limit field. The technique thus counters the LSB pattern even in case of a pattern variation to different network protocols. The LSB pattern could also be applied to the BACnet NPDU hop count field -no new normalization technique must be implemented for the same pattern.
Fisk et al. mention general cases for the application of traffic normalization [Fisk et al. 2003]. For instance, unused fields can be cleared (Reserved/Unused pattern); decreasing fields (like the TTL) can be set to fixed values (LSB pattern and Value Modulation pattern); and derivate fields (i.e. those depending on other fields, like the Checksum or the Internet Header Length in IPv4) can be re-placed with correct values or the particular packets can be dropped (PDU Corruption/Loss pattern). Such general applications of normalization rules can be used in a protocol-independent manner and are thus capable of countering a whole set of hiding techniques which are based on the same pattern.

Illustration: Protocol Switching-aware Active Warden
The aforementioned PCAW [Wendzel and Keller 2012a] introduces delays on protocol switches and thus limits the bitrate of covert channels that signal hidden information through the use of particular network protocols. As shown in [Wendzel and Keller 2012a], the PCAW cannot only be successfully applied to protocol switching covert channels based on IPv4 but also to building automation networks using BACnet and thus exemplifies the variation of countermeasures as well.

CONCLUSION
We evaluated 109 network covert channel techniques from the last decades and extracted abstract patterns from these techniques. We were able to represent all 109 techniques by 11 patterns which we arranged in a hierarchical catalog based on the Pattern Language Markup Language (PLML). Moreover, we showed that the majority of these techniques can be reduced to only four different patterns -evidence that many network covert channel techniques invented represent very similar techniques.
The pattern catalog will be provided on-line in order to allow the scientific community to modify and extend the covert channel pattern collection. Our catalog eases the novelty evaluation of future covert channel techniques.
We presented the concept of pattern variation for covert channels. Pattern variation allows the automatic adaption of the generic hiding technique to different network protocols without requiring a re-implementation of the technique itself. Since covert channels are a dual-use good, we also introduced the pattern-based approaches pattern hopping and pattern combination to improve the throughput and stealthiness of covert channels.
If prevention approaches counter generic patterns instead of hiding techniques, the number of necessary countermeasures is greatly reduced. Under the assumption that future techniques for covert channels will often fall into one of the existing pattern categories, the value of our pattern-based approach increases even further.
Future work will comprise the generation of a PLML-based pattern catalog for local covert channels and for steganographic network channels as well as the evaluation of countermeasures for local and steganographic network channels against the particular patterns.The Ninth Circuit Court on Monday ordered the Obama Administration to take a definite position on whether it will defend the constitutionality of the Pentagon’s existing “don’t ask/don’t tell” policy against gays and lesbians serving openly in the military.Â In a new order, the three-judge Circuit Court panel indicated it may let someone else come to the defense of that policy, if the government doesn’t.Â But it also raised the prospect that it will end the case over the constitutional question abruptly, perhaps later this summer.
In the new order, the panel that will decide the case noted that “the United States is not prepared to defend the constitutionality” of the 1993 law.Â That, though, is the only law at issue before the Circuit Court, it noted.Â “The central issue this court must address,” it said, was the constitutionality of the existing law, not the repeal law, and yet no party involved in the case is willing to defend what Congress enacted in 1993.
To sort all of this out, the panel ordered the government to advise it within ten days whether it will formally abandon any defense of the law, and, if it does, whether it will do so in time to enable Congress to take up the defense and join in the Circuit Court’s review.Â Â But, in the final part of the order, the panel told the parties in the case to offer reasons why the case should not be dismissed as moot, now or when the repeal law actually takes effect.Â Under the repeal law, its effective date is to come 60 days after the President, the Defense Secretary, and the nation’s top military officer formally certify that the military is ready to implement the law.
All of the responses the panel ordered are due in ten days.
Q: How to make sure an Android app was really compiled from said source code? A lot of Android apps are open source, but how can we make sure the person who finally uploads to the Google Market does not include some spyware just before uploading?
Background: Mobile apps security seems to be a growing concern, and I would like to reassure the users of my Open Source Android app. Solutions that require to modify the deployment process or application content are acceptable too.
2012 update: This is going in the right direction: http://f-droid.org/ They check the apps and compile them into APKs that they distribute. That being said, I would trust them more 
if they were Mozilla or Apache...

A: Take a look at https://stackoverflow.com/questions/249106/how-can-you-give-users-confidence-that-your-application-has-no-malicious-intent for some related information.
You could of course take the source and build/compile it yourself and compare the resulting binary to the uploaded one, but this somehow defeats the purpose of binary distribution. And it still wouldn't help in cases where the source code does contain malicious code. Or maybe build a safe, i.e. trusted reference binary and then publish the checksum for comparison?
Apart from that, this problem really is not specific to open source software. In the end, it all boils down to trust.
How do I actually cope so I don't lose day after day to my illness. I'm really struggling.

When in psychosis and I have nobody to talk to (my family was toxic anyway, but they all ditched me, I can't get over it, it hurts and consumes me), what should I do with my self? Im scared to do anything. I never feel safe or comfortable. I always feel off or blunted.  I never have. Ive been alone a lot and have serious doubts that there are any people who could ever not hate me or want me to be around. I am not like them and they want to be cruel when they see me. Because of this apparent fact, I typically will make myself look pretty hardcore.  So that isn't really who I am. And I hate doing it. But the only other way I am is a person that is too timid and nervous and shy, way too nice.  Not by choice. I would do anything to have one good friend. Like someone who has actual