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A large number of today’s botnets leverage the HTTP protocol to communicate with their botmasters or perpetrate malicious activities. In this paper, we present a new scalable system for network-level behavioral clustering of HTTP-based malware that aims to efficiently group newly collected malware samples into malware family clusters. The end goal is to obtain malware clusters that can aid the automatic...
Network intrusion detection systems (NIDSs), especially signature-based NIDSs, are being widely deployed in a distributed network environment with the purpose of defending against a variety of network attacks. However, signature matching is a key limiting factor to limit and lower the performance of a signature-based NIDS in a large-scale network environment, in which the cost is at least linear to...
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