DocumentCode :
3213469
Title :
System and methodology for unknown Malware attack
Author :
Murugan, S. ; Kuppusamy, K.
Author_Institution :
ACTS Coordinator, Bangalore, India
fYear :
2011
fDate :
20-22 July 2011
Firstpage :
803
Lastpage :
804
Abstract :
Intrusion Detection Prevention Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection prevention are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection. The techniques that are being investigated includes neural networks and fuzzy logic with network profiling, that uses simple data mining techniques to process the network data. The proposed system is a hybrid system that combines anomaly, misuse and host based detection.
Keywords :
data mining; fuzzy logic; invasive software; neural nets; anomaly detection; artificial intelligence; data mining technique; fuzzy logic; host based detection; intrusion detection prevention system; misuse detection; network profiling; neural network; unknown malware attack; Data mining; Fuzzy Logic; Intrusion Detection; Network Security;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Sustainable Energy and Intelligent Systems (SEISCON 2011), International Conference on
Conference_Location :
Chennai
Type :
conf
DOI :
10.1049/cp.2011.0475
Filename :
6143424
Link To Document :
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