Title :
An Application of Learning Problem in Anomaly-based Intrusion Detection Systems
Author :
Jecheva, Veselina G. ; Nikolova, Evgeniya P.
Author_Institution :
Burgas Free Univ.
Abstract :
The present paper introduces an approach to anomaly-based intrusion detection using the hidden Markov models (HMM) and the BCJR decoding algorithm. The main idea is to distinguish the normal traces of user activity from abnormal ones using the BCJR decoding algorithm applied in conjunction with HMM parameters adjustment using the gradient based method. Some results from the conducted simulation experiments are introduced as well
Keywords :
gradient methods; hidden Markov models; learning (artificial intelligence); security of data; BCJR decoding algorithm; anomaly-based intrusion detection systems; gradient based method; hidden Markov models; learning; user activity; Automata; Databases; Decoding; Hidden Markov models; Intrusion detection; Pattern matching; Pattern recognition; Protection; Sequences; Specification languages;
Conference_Titel :
Availability, Reliability and Security, 2007. ARES 2007. The Second International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2775-2
DOI :
10.1109/ARES.2007.35
