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Previous research has shown that byte-level analysis of network traffic can be useful for network intrusion detection and traffic analysis. Such an approach does not require any knowledge of applications running on web servers or any pre-processing of incoming data.In this paper, we apply three n-gram techniques to the problem of HTTP attack detection. The goal is to provide a first line of defense...
Recent work has presented hidden Markov models (HMMs) as a compelling option for virus identification. However, to date little research has been done to identify the meaning of these hidden states. In this paper, we examine HMMs for four different compilers, hand-written assembly code, three virus construction kits, and a metamorphic virus in order to note similarities and differences in the hidden...
In this paper, we consider the problem of masquerade detection, based on user-issued UNIX commands. We present a novel detection technique based on profile hidden Markov models (PHMMs). For comparison purposes, we implement an existing modeling technique based on hidden Markov models (HMMs). We compare these approaches and show that, in general, our PHMM technique is competitive with HMMs. However,...
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