article · 2008

Learning Problem and BCJR Decoding Algorithm in Anomaly-based Intrusion Detection Systems

Cited by 0Abstract and details only

Abstract

Abstract — The anomaly-based intrusion detection systems examine current system activity do find deviations from normal system activity. The present paper proposes a method for normal activity description using the Hidden Markov Models (HMM), which is tuned up using the gradient based method. The obtained model is utilized as a baseline, depicting the normal system activity. The main purpose is to distinguish the normal traces of user activity from abnormal ones using the BCJR decoding algorithm. Some results from the conducted simulation experiments are introduced as well. Index Terms — intrusion detection, anomaly-based intrusion detection, learning problem, Hidden Markov Model, BCJR decoding algorithm.

Cite this paper

APA 7

(2008). Learning Problem and BCJR Decoding Algorithm in Anomaly-based Intrusion Detection Systems.

MLA 9

“Learning Problem and BCJR Decoding Algorithm in Anomaly-based Intrusion Detection Systems.” 2008.

Chicago

2008. “Learning Problem and BCJR Decoding Algorithm in Anomaly-based Intrusion Detection Systems.”

Harvard

(2008) ‘Learning Problem and BCJR Decoding Algorithm in Anomaly-based Intrusion Detection Systems’.

BibTeX

@article{anon2008learning,
  title = {{Learning Problem and BCJR Decoding Algorithm in Anomaly-based Intrusion Detection Systems}},
  year = {2008}
}

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