Download now Free registration required
Conventional approaches to intrusion detection system pose a myriad of problems that exhibit serious impediments to the degree of configurability, extensibility, and effectiveness of the systems. The proposed methodology is a combination of three techniques comprising two machine-learning paradigms. KMeans Clustering, Fuzzy Logics and Neural Network techniques deployed to configure an effective intrusion detection system. Out of the several problems in the traditional techniques of Intrusion Detection Systems, the presence of high rate of false alerts causes unnecessary interference of human analyst. The human analysts in turn perform an intensive analysis repeatedly to distinguish the nature of such alerts and initiate sufficient actions.
- Format: PDF
- Size: 82.8 KB