文章基本信息

标题：Intrusion Detection Algorithm for data security
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作者：Neeraj Kumar ; Dr. Upendra Kumar ; Dr. G. Sahoo 等
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2015
卷号：29
期号：3
页码：157-160
DOI：10.14445/22312803/IJCTT-V29P127
出版社：Seventh Sense Research Group
摘要：Rapid development in Network Technologies system in this I.T. era huge flow of data from network every moment, so obviously there should be a strong Network Intrusion Detection system (NIDS)is an important detection system that is used as a counter measure to prevent data integrity and system availability from attack [14] or a robust mechanism require to distinguish between relevant and nonrelevant data particularly acting as an attack. Thus to provide total network security from intrusion this paper contributed to propose a innovative Intrusion Detection Algorithm (HDensities of data points known as Hamming density. Hamming density [8] is knearest neighbor divided by Hammingdistance) Density based Outlier Detection in data mining on UCI repository KDD Cup’99(Network Intrusion) data set. Simulation and Compare the result in finding the intrusion by our propose DBOD from other exiting algorithms like LOF in own Simulator and found comparatively more accuracy and increase in detecting the number of Intrusion in our proposed work.
关键词：Hamming Distance; Outliers; OutlierDetection.