Exhaust: Optimizing Wu-Manber pattern matching for intrusion detection using Bloom filters
Document Type
Conference Proceeding
Source of Publication
2015 2nd World Symposium on Web Applications and Networking, WSWAN 2015
Publication Date
1-1-2015
Abstract
© 2015 IEEE. Intrusion detection systems are widely accepted as one of the main tools for monitoring and analyzing host and network traffic to protect data from illegal access or modification. Almost all types of signature-based intrusion detection systems must employ a pattern matching algorithm to inspect packets for malicious signatures. Unfortunately, pattern matching algorithms dominate the execution time and have become the bottleneck. To remedy that, we introduce a new software-based pattern matching algorithm that modifies Wu-Manber pattern matching algorithm using Bloom filters. The Bloom filter acts as an exclusion filter to reduce the number of searches to the large HASH table. The HASH table is accessed if there is a probable match represented by a shift value of zero. On average the HASH table search is skipped 10.6% of the time with a worst case average running time speedup over Wu-Manber of 33%. The maximum overhead incurred on preprocessing time is 1.1% and the worst case increase in memory usage was limited to 0.33%.
DOI Link
ISBN
9781479981717
Publisher
Institute of Electrical and Electronics Engineers Inc.
Last Page
6
Disciplines
Computer Sciences
Keywords
Bloom Filters, Intrusion Detection Systems, Network Security, Pattern Matching, Wu-Manber
Scopus ID
Recommended Citation
Aldwairi, Monther and Al-Khamaiseh, Koloud, "Exhaust: Optimizing Wu-Manber pattern matching for intrusion detection using Bloom filters" (2015). All Works. 1578.
https://zuscholars.zu.ac.ae/works/1578
Indexed in Scopus
yes
Open Access
no