Variable Length Pattern Matching for Hardware Network Intrusion Detection System

  • Authors:
  • Chun Jason Xue;Meilin Liu;Qingfeng Zhuge;Edwin Hsing-Mean Sha

  • Affiliations:
  • Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong;Department of Computer Science and Engineering, Wright State University, Dayton, USA 45435;Department of Computer Science, University of Texas at Dallas, Richardson, USA 75083;Department of Computer Science, University of Texas at Dallas, Richardson, USA 75083

  • Venue:
  • Journal of Signal Processing Systems
  • Year:
  • 2010

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Abstract

With the wide adoption of internet into our everyday lives, internet security becomes an important issue. Intrusion detection at the network level is an effective way of stopping malicious attacks at the source and preventing viruses and worms from wide spreading. The key component in a successful network intrusion detection system is a high performance pattern matching engine that can uncover the malicious activities in real time. In this paper, we propose a highly parallel, scalable hardware based network intrusion detection system, that can handle variable pattern length efficiently and effectively. Pattern matching for a packet is completed in O(N log M) time where N is the size of the packet and M is the longest pattern length. Implementation is done on a standard off-the-shelf field-programmable gate array. Comparison with the other techniques shows promising results.