Download Computer Security – ESORICS 2016: 21st European Symposium on by Ioannis Askoxylakis, Sotiris Ioannidis, Sokratis Katsikas, PDF

By Ioannis Askoxylakis, Sotiris Ioannidis, Sokratis Katsikas, Catherine Meadows

The two-volume set, LNCS 9878 and 9879 constitutes the refereed lawsuits of the twenty first eu Symposium on learn in computing device defense, ESORICS 2016, held in Heraklion, Greece, in September 2016.

The 60 revised complete papers awarded have been conscientiously reviewed and chosen from 285 submissions. The papers disguise quite a lot of issues in safety and privateness, together with info safety: structures safety, community defense, entry keep an eye on, authentication, and safety in such rising components as cloud computing, cyber-physical structures, and the web of Things.

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Additional resources for Computer Security – ESORICS 2016: 21st European Symposium on Research in Computer Security, Heraklion, Greece, September 26-30, 2016, Proceedings, Part I

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Overhead but causes the pages become less distinguishable and thereby reduces the attacker’s accuracy. We created a statistical model of the underlying distributions of inter-arrival times from the samples we extracted from our dataset. We experimented with multiple positively skewed distributions to build the model and test the goodness of fit with the Kolmogorov-Smirnov test. We estimated the parameters of the distributions using maximum likelihood estimation. Even though Pareto and Beta distributions seemed to fit best, we decided for simplicity to use normal and log-normal distributions, given that the error was not significantly greater than that observed in the other distributions.

Then, the attacker aims to identify the exact monitored pages the user visits and to classify all the visits to non-monitored pages into the non-monitored class regardless of the actual page. We observe that even though the accuracy initially increases as the world grows and saturates to 95 % at the maximum considered world size, the F1Score decreases and levels off to 50 %. This is because even though the FPR rapidly drops to zero, the TPR decreases below 40 %. The accuracy is so high because the classifier reaches almost perfect classification for the non-monitored class.

37] analyzed malicious cellular DNS traffic generated by mobile applications to conclude that mobile app-level protection (eg. app-market security) suffices to curtail mobile attacks. Our work shows that the emergent cross-channel abuse strategy bypasses this and is a more serious threat to mobile users. Key Differences: In summary, much of the past work in SMS abuse has focused on the analysis of call detail records to identify spam source phone numbers rather than on the characterization of the network infrastructure that facilitates the abuse.

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