Finite Automata Models for Anomaly Detection

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dc.contributor.advisorBaras, John S.en_US
dc.contributor.authorRamezani, Vahiden_US
dc.contributor.authorYang, Shah-Anen_US
dc.contributor.authorBaras, John S.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:12:09Z
dc.date.available2007-05-23T10:12:09Z
dc.date.issued2002en_US
dc.description.abstractA fundamental problem in intrusion detection is the fusion of dependent information sequences. In this paper, we consider the fusion of twosuch sequences, namely the sequences of system calls and thevalues of the instruction pointer. We introduce FAAD, a finite automatonrepresentation defined for the product alphabet of the two sequences wheredependencies are implicitly taken into account by a matchingprocedure. Our learning algorithm captures these dependencies through the application of certain parameterized functions. Through thechoice of thresholds and inner product structures, we areable to produce a compact representation of thenormal behavior of program.en_US
dc.format.extent124443 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/6275
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 2002-42en_US
dc.subjectGlobal Communication Systemsen_US
dc.titleFinite Automata Models for Anomaly Detectionen_US
dc.typeTechnical Reporten_US

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