Affiliation:
1. Taher Moulay University of Saida, Algeria
2. Djillali Liabes University of Sidi Bel Abbes, Algeria
Abstract
Given the increasing number of users of computer systems and networks, it is difficult to know the profile of the latter, and therefore, intrusion has become a highly prized area of network security. In this chapter, to address the issues mentioned above, the authors use data mining techniques, namely association rules, decision trees, and Bayesian networks. The results obtained on the KDD'99 benchmark have been validated by several evaluation measures and are promising and provide access to other techniques and hybridization to improve the security and confidentiality in the field.
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