Combating Cyber Security Breaches in Digital World Using Misuse Detection Methods: Misuse Detection

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Author(s): Subbulakshmi T. (VIT University, India)
Copyright: 2016
Pages: 8
Source title: Combating Security Breaches and Criminal Activity in the Digital Sphere
Source Author(s)/Editor(s): S. Geetha (Vellore Institute of Technology, India)and Asnath Victy Phamila (Vellore Institute of Technology, Chennai, India)
DOI: 10.4018/978-1-5225-0193-0.ch006

Keywords: Cyber and Network Security / Information Science Reference / Information Security & Privacy / Security & Forensics

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Abstract

Intrusion Detection Systems (IDS) play a major role in the area of combating security breaches for information security. Current IDS are developed with Machine learning techniques like Artificial Neural Networks, C 4.5, KNN, Naïve Bayes classifiers, Genetic algorithms Fuzzy logic and SVMs. The objective of this paper is to apply Artificial Neural Networks and Support Vector Machines for intrusion detection. Artificial Neural Networks are applied along with faster training methods like variable learning rate and scaled conjugate gradient. Support Vector Machines use various kernel functions to improve the performance. From the kddcup'99 dataset 45,657 instances are taken and used in our experiment. The speed is compared for various training functions. The performance of various kernel functions is assessed. The detection rate of Support Vector Machines is found to be greater than Artificial Neural Networks with less number of false positives and with less time of detection.

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Combating Cyber Security Breaches in Digital World Using Misuse Detection Methods: Misuse Detection

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