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Author/Affiliation: Ken FerensA Support Vector Machine Cost Function in Simulated Annealing for Network Intrusion Detection
This paper proposes a computationally intelligent algorithm for extracting relevant features from a training set. An optimal subset of features is extracted from training examples of network intrusion datasets. The Support Vector Machine (SVM) algorithm is used as the cost function within the thermal equilibrium loop of the Simulated Annealing (SA) algorithm. The proposed fusion…
Read MoreA Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks
A wormhole attack is one of the most critical and challenging security threats for wireless sensor networks because of its nature and ability to perform concealed malicious activities. This paper proposes an innovative wormhole detection scheme to detect wormhole attacks using computational intelligence and an artificial neural network (ANN). Most wormhole detection schemes reported in…
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