期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2012
卷号：3
期号：2
页码：991-994
语种：English
出版社：Ayushmaan Technologies
摘要：This paper discuses about research in developing general and systematic methods for intrusion detection in MANET and based on the classification elect the leaders in network. A MANET can be defined as dynamic peer-to-peer network that consist of a collection of mobile nodes and are characterized by great flexibility and are employed in a broad range of applications. The key ideas are to use data mining techniques to discover consistent and useful patterns of system features that describe program and user behavior. By using the set of relevant system features to compute classifiers that can recognize anomalies known as intrusions. The performance of the classification algorithms is evaluated under different traffic conditions and mobility patterns for the blackhole, forging, packet dropping and flooding attacks. The results indicate that SVM exhibit high accuracy for almost all simulated attacks. The packet dropping attack is most difficult to detect.
