An Optimized Genetic Algorithm with Classification Approach used for Intrusion Detection
作者: Aliakbar Tajari Siahmarzkooh Saied Tabarsa Ziba Hosseini NasabFareevar Sedighi
刊名: International Journal of Computer Networks and Communications Security (IJCNCS), 2015, Vol.3 (1)
来源数据库: Dorma Trading, Est. Publishing Manager
关键词: Intrusion Detection SystemNaïve BayesSupport Vector MachineGenetic AlgorithmKDDCup99 datasetFalse alarm Rates
原始语种摘要: IDSs which are increasingly a key part of system defense are used to identify abnormal activities in a computer system. In general, the traditional intrusion detection relies on the extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been used in the literature. During recent years, number of attacks on networks has dramatically increased and consequently interest in network intrusion detection has increased among the researchers. In this paper we have used the terms detection rates and false alarm rates to compare the results of Naïve Bayes algorithm and Support Vector Machine algorithm to find out the results for intrusion detections and...
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  • intrusion 侵入
  • network 网络
  • alarm 警报
  • computer 电子计算机
  • algorithm 算法
  • protected 防护的
  • detection 探测
  • technique 技术
  • security 可靠性
  • knowledge 知识