Cognitive Approach Based User Node Activity Monitoring for Intrusion Detection in Wireless Networks
Cognitive networks are the solution for the problems existing on the current networks. Users maintain integrity of the networks and user node activity monitoring is required for provision of security. Cognitive Networks discussed in this paper not only monitor user node activity but also take preventive measures if user node transactions are malicious. The intelligence in cognitive engine is realized using self-organizing maps (CSOMs). Gaussian and Mexican Hat neighbor learning functions have been evaluated to realize CSOMs. Experimental study proves the efficiency of Gaussian Learning function is better for cognition engine. The cognition engine realized is evaluated for malicious node detection in dynamic networks. The proposed concept results in better Intrusion detection rate as compared to existing approaches.
Keywords: Intrusion Detection, Cognitive networks, Soft computing, Self-organizing maps, Computational intelligence.
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ABOUT THE AUTHORS
G Sunilkumar
University Visvesvaraya College of Engineering, Bangalore University
Thriveni J
University Visvesvaraya College of Engineering, Bangalore University
K R Venugopal
University Visvesvaraya College of Engineering, Bangalore University
L M Patnaik
Defence Institute of Advanced Technology Pune, India
G Sunilkumar
University Visvesvaraya College of Engineering, Bangalore University
Thriveni J
University Visvesvaraya College of Engineering, Bangalore University
K R Venugopal
University Visvesvaraya College of Engineering, Bangalore University
L M Patnaik
Defence Institute of Advanced Technology Pune, India