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ACSAC
2003
IEEE

Intrusion Detection: A Bioinformatics Approach

12 years 1 months ago
Intrusion Detection: A Bioinformatics Approach
This paper addresses the problem of detecting masquerading, a security attack in which an intruder assumes the identity of a legitimate user. Many approaches based on Hidden Markov Models and various forms of Finite State Automata have been proposed to solve this problem. The novelty of our approach results from the application of techniques used in bioinformatics for a pair-wise sequence alignment to compare the monitored session with past user behavior. Our algorithm uses a semi-global alignment and a unique scoring system to measure similarity between a sequence of commands produced by a potential intruder and the user signature, which is a sequence of commands collected from a legitimate user. We tested this algorithm on the standard intrusion data collection set. As discussed in the paper, the results of the test showed that the described algorithm yields a promising combination of intrusion detection rate and false positive rate, when compared to published intrusion detection al...
Scott E. Coull, Joel W. Branch, Boleslaw K. Szyman
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ACSAC
Authors Scott E. Coull, Joel W. Branch, Boleslaw K. Szymanski, Eric Breimer
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