Abstract
The paper content is genetic algorithm based intrusion detection system. It is a simulation type system comes under networking area. The first system in the line is an anomaly-based IDS implemented as a simple linear classifier. This system exhibits high both detection and false-positive rate. For that reason, we have added a simple system based on if-then rules that filter the decision of the linear classifier and in that way significantly reduces false-positive rate. In the first step of our solution we deploy feature extraction techniques in order to reduce the amount of data that the system needs to process. Hence, our system is simple enough not to introduce significant computational overhead, but at the same time is accurate, adaptive and fast due to genetic algorithms. The model is verified on KDD99 benchmark dataset.
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Gupta, P., Shinde, S.K. (2011). Genetic Algorithm Technique Used to Detect Intrusion Detection. In: Wyld, D.C., Wozniak, M., Chaki, N., Meghanathan, N., Nagamalai, D. (eds) Advances in Computing and Information Technology. ACITY 2011. Communications in Computer and Information Science, vol 198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22555-0_14
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DOI: https://doi.org/10.1007/978-3-642-22555-0_14
Publisher Name: Springer, Berlin, Heidelberg
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