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This paper addresses the problem of detecting the presence of malware that leaveperiodictraces innetworktraffic. This characteristic behavior of malware was found to be surprisingly prevalent in a parallel study. To this end, we propose a visual analytics solution that supports both automatic detection and manual inspection of periodic signals hidden in network traffic. The detected periodic signals...
We notice, in our experiments with three malware samples of Darkcomet, Andromeda, and Zeus, that all three of them generate highly periodic network traffic. In addition, while there are a few works on intrusion detection which are based on this periodic behavior of malware, the prevalence of this behavior among the malware families in the wild is unknown. In this paper, we conduct an extensive experimental...
The increased computation and storage capabilities of smartphones have attracted more and more cybercriminals to write mobile malware for different purposes. Due to the popularity of smartphones in both personal life and business, it is empowering an emerging mobile security threat issue. In this paper, we present an intrusion detection system that incorporates not only network features but also host-based...
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