期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2017
卷号：50
期号：1
页码：43-49
DOI：10.14445/22312803/IJCTT-V50P107
出版社：Seventh Sense Research Group
摘要：Consequent upon the growth of Internet and multifarious technologies including smart devices and their massive use and operations on Internet platform not only caused serious threats on security but also abnormal traffic detection. A number of assorted attacks on Internet seriously affect the systems. This not only leads to deteriorate the performance in the computer but also malfunctioning of the system. Vast growth of data in various areas due to adoption of computer technologies precipitated to anomalies. Thus, in such an alarming situation, anomalous traffic detection became a major concern of the security. Intrusion detection system is one of the redressed techniques that can be employed to determine the system security which detects the intrusion. In this paper performance of NSLKDD dataset has been evaluated using LVQ, RBFN, DECR_RBFN, EVRBFN, MLP_BP, SONN networks of ANN showing the results that constitute binary class. Based on various performance measures analytical results were derived.
