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With fast growing cyber activities everyday, cyber attack has become a critical issue over the last decade. A number of cyber attack detection algorithms have been developed and applied in this field of study with different levels of success. In this paper, a new distributed cyber attack detection algorithm based on the decision cost minimization strategy is introduced. The proposed algorithm employs...
Feature selection attracted much interest from researchers in many fields such as network security, pattern recognition and data mining. In this paper, we present a wrapper-based feature selection algorithm aiming at modeling lightweight intrusion detection system (IDS) by (1) using modified random mutation hill climbing (MRMHC) as search strategy to specify a candidate subset for evaluation; (2)...
The intrusion detection system deals with huge amount of data which contains irrelevant and redundant features causing slow training and testing process, higher resource consumption as well as poor detection rate. Feature selection, therefore, is an important issue in intrusion detection. An appropriate feature set obtained by feature selection can help to build lightweight intrusion detection system...
An appropriate feature set helps to build efficient decision model as well as reduced feature set lights up the training and testing process considerably. In this paper, we propose a new approach to build efficient Intrusion detection system (IDS) based on principal component analysis and C4.5. Our method is able to significantly decrease training and testing times while retaining high detection rates...
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