Mobile botnet phenomenon is gaining popularity among malware writers in order to exploit vulnerabilities in smartphones. In particular, mobile botnets enable illegal access to a victim’s smartphone, can compromise critical user data and launch a DDoS attack through Command and Control (C&C). In this article, we propose a static analysis approach, DeDroid, to investigate botnet-specific properti...

Attackers are increasingly using large networks of compromised machines to carry out further attacks (e.g., using botnets, or enormous groups of compromised hosts under the control of a single attacker). We consider the problem of responding to entire networks of attacking computers. We identify key metrics for measuring the utility of a botnet, and describe various topological structures they ...

Botnets have become a major threat to the Internet as large armies of bot machines can be used to carry out a wide range of attacks. We present a botnet detection mechanism that uses two levels of support vector machines (SVMs) to identify infected bot machines before they are used in an attack. Our technique detects relationships in the networkflows dynamically and determines if such relations...

Application layer Distributed Denial of Service (DDoS) attacks are recognized as one of the most damaging attacks on the Internet security today. In our recent work [1], we have shown that unsupervised machine learning can be effectively utilized in the process of distinguishing between regular (human) and automated (web/botnet crawler) visitors to a web site. We have also shown that with a sli...

Contents 1 Questions and methodology 6 1. 5 How do member ISPs compare among themselves? 47 6 Conclusions 55 6.

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