DocumentCode :
2141540
Title :
Real time intrusion prediction, detection and prevention programs
Author :
Abraham, Ajith
Author_Institution :
Norwegian Center of Excellence, Norwegian Univ. of Sci. & Technol., Trondheim
fYear :
2008
fDate :
17-20 June 2008
Abstract :
An intrusion detection program (IDP) analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. In this talk, we present some of the challenges in designing efficient intrusion detection systems (IDS) using nature inspired computation techniques, which could provide high accuracy, low false alarm rate and reduced number of features. Then we present some recent research results of developing distributed intrusion detection systems using genetic programming techniques. Further, we illustrate how intruder behavior could be captured using hidden Markov model and predict possible serious intrusions. Finally we illustrate the role of online risk assessment for intrusion prevention systems and some associated results.
Keywords :
genetic algorithms; hidden Markov models; risk management; security of data; distributed intrusion detection systems; genetic programming; hidden Markov model; intrusion detection program; online risk assessment; real time intrusion detection; real time intrusion prediction; real time intrusion prevention; Competitive intelligence; Computational intelligence; Data mining; Data security; Hidden Markov models; Hybrid intelligent systems; Information security; Intrusion detection; Risk management; Web services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligence and Security Informatics, 2008. ISI 2008. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2414-6
Electronic_ISBN :
978-1-4244-2415-3
Type :
conf
DOI :
10.1109/ISI.2008.4565018
Filename :
4565018
Link To Document :
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