期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：3
页码：6040
DOI：10.15680/IJIRCCE.2017.0503360
出版社：S&S Publications
摘要：Now a day’s usage of internet and world wide connectivity has been grown, well-proportionate withcyber attacks. With the level of automation in attack tools, attacks are increased continuously, the information requiresto infringe the security is minimized and the complication also increases proportionally which make the tasks ofsecurity professional very intricate. Maintaining Cyber security is a severe universal fright. Intrusion Detection System(IDS) has turn out to be an indispensable part of system security to identify several attacks with an intension ofshielding systems from extensive harms and recognizing risks of the intruded system. Therefore finding intrusionsaccurately becomes chief functionality of most Intrusion Detection Systems. IDS can be seen or analysed as ananomaly based and signature based IDS. Here in this paper we are throwing light on anomaly based Intrusion DetectionSystem. The considered concepts for anomaly based intrusion detection system are apache storm, neural network,artificial immune system, genetic clustering method and Linear Discriminant Analysis & Logistic Regression. All theseconcepts are compared based on the detection rate and false positive rate value for anomaly based intrusion detectionsystem.
