DocumentCode
260063
Title
Modified Apriori Approach for Evade Network Intrusion Detection System
Author
Lahoti, Laxmi ; Chandankhede, Chaitali ; Mukhopadhyay, Debajyoti
Author_Institution
Dept. of Inf. Technol., MIT, Pune, India
fYear
2014
fDate
22-24 Dec. 2014
Firstpage
374
Lastpage
378
Abstract
Intrusion Detection System (IDS) is a software or hardware tool that repeatedly scans and monitors events that took place in a computer or a network. A set of rules are used by Signature based Network Intrusion Detection Systems (NIDS) to detect hostile traffic in network segments or packets, which are so important in detecting malicious and anomalous behavior over the network like known attacks that hackers look for new techniques to go unseen. Sometime, a single failure at any layer will cause the NIDS to miss that attack. To overcome this problem, a technique is used that will trigger a failure in that layer. Such technique is known as Evasive technique. An Evasion can be defined as any technique that modifies a visible attack into any other form in order to stay away from being detect. The proposed system is used for detecting attacks which are going on the network and also gives actual categorization of attacks. The proposed system has advantage of getting low false alarm rate and high detection rate. So that leads into decrease in complexity and overhead on the system. The paper presents the Evasion technique for customized apriori algorithm. The paper aims to make a new functional structure to evade NIDS. This framework can be used to audit NIDS. This framework shows that a proof of concept showing how to evade a self-built NIDS considering two publicly available datasets.
Keywords
computer crime; computer network security; actual attack categorization; anomalous behavior; customized apriori algorithm; evade network intrusion detection system; evasion technique; hackers; hardware tool; hostile traffic; malicious behavior; modified apriori approach; network packets; network segments; self-built NIDS; software tool; visible attack; Classification algorithms; Computers; Information technology; Intrusion detection; Machine learning algorithms; Monitoring; Evasion; Intrusion detection; Network intrusion detection system; Network security;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology (ICIT), 2014 International Conference on
Conference_Location
Bhubaneswar
Print_ISBN
978-1-4799-8083-3
Type
conf
DOI
10.1109/ICIT.2014.17
Filename
7033353
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