Title: Intrusion detection system design of cloud computing based on abnormal traffic identification

Authors: Sunan Wang; Yingying Li; Xin Zhao; Bin Wang

Addresses: School of Electronics and Communication Engineering, Zhejiang University, Hangzhou, 310058, China; School of Electronics and Communication Engineering, Shenzhen Polytechnic, Shenzhen, 518055, China ' School of Electronics and Communication Engineering, Shenzhen Polytechnic, Shenzhen, 518055, China ' School of Electronics and Communication Engineering, Zhejiang University, Hangzhou, 310058, China ' School of Electronics and Communication Engineering, Zhejiang University, Hangzhou, 310058, China

Abstract: With the ever increasing network security risk factor, network intrusion detection information needed to solve many computational costs, timeliness of a series of technical problems. This article analysed the background of intrusion detection system, generalising the high performance network invade to examine the technique research development condition, then put forward a new intrude detection system of cloud calculate network. Using cloud computing platform, we can quickly detect anomaly network traffic and intrusion detection data. It not only extends the system administrator's security management capabilities, including security auditing, monitoring, attack recognition and traceability, but also improve information security system's integrity and availability.

Keywords: network security; intrusion detection; detection policy; abnormal traffic identification; cloud computing; security management; security auditing; monitoring; attack recognition; traceability; integrity; availability.

DOI: 10.1504/IJRIS.2015.072945

International Journal of Reasoning-based Intelligent Systems, 2015 Vol.7 No.3/4, pp.186 - 192

Received: 21 Nov 2014
Accepted: 11 Dec 2014

Published online: 09 Nov 2015 *

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