NSA SoS Lablets Materials
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Submitted by awhitesell on Wed, 07/13/2016 - 1:56pm
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Submitted by awhitesell on Wed, 07/13/2016 - 1:48pm
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Submitted by awhitesell on Tue, 04/12/2016 - 3:46pm
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Submitted by awhitesell on Tue, 04/12/2016 - 3:40pm
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The prevalence of smart devices has promoted the popularity of mobile applications (a.k.a. apps) in recent years. A number of interesting and important questions remain unanswered, such as why a user likes/dislikes an app, how an app becomes popular or eventually perishes, how a user selects apps to install and interacts with them, how frequently an app is used and how much trac it generates, etc. This paper presents an empirical analysis of app usage behaviors collected from millions of users of Wandoujia, a leading Android app marketplace in China.
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Abstract--Recent attacks show that threats to cyber infrastructure are not only increasing in volume, but are getting more sophisticated. The attacks may comprise multiple actions that are hard to differentiate from benign activity, and therefore common detection techniques have to deal with high false positive rates. Because of the imperfect performance of automated detection techniques, responses to such attacks are highly dependent on human-driven decision-making processes.
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Reliability block diagram (RBD) models are a commonly used reliability analysis method. For static RBD models, combinatorial solution techniques are easy and ecient. However, static RBDs are limited in their ability to express varying system state, dependent events, and non-series-parallel topologies. A recent extension to RBDs, called Dynamic Reliability Block Diagrams (DRBD), has eliminated those limitations.
