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Network security risks grow tremendously in recent past; the attacks on computer networks have enhanced hugely and need economical network intrusion detection mechanisms. Data processing and machine-learning techniques are used for network intrusion detection throughout the past few years and have gained abundant quality. In this paper, the authors propose an intrusion detection mechanism based on Simplified particle Swarm Optimization (SSO) is used to investigate the performance of various dimension reduction techniques along with a set of different classifiers including the proposed approach.
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