HashTrie: a space-efficient multiple string matching algorithm

• Published in: Tongxin Xuebao Vol. 36; no. 10; pp. 2015215 - 2015219
• Main Authors: Zhang, Ping, Liu, Yan-Bing, Yu, Jing, Tan, Jian-Long
• Format: Journal Article
• Language: Chinese
• Published: Editorial Department of Journal on Communications 01.10.2015
• Subjects: Algorithms; bit-vector; Complexity; Consumption; intrusion detection; multiple string matching; recursive hash function; Searching; Signatures; space-efficient; Stores; String matching; Strings
• ISSN: 1000-436X
• DOI: 10.11959/j.issn.1000-436x.2015215

The famous multiple string matching algorithm AC consumed huge memory when the string signatures were massive, thus unable to process high speed network traffic efficiently. To solve this problem, a space-efficient multiple string matching algorithm-HashTrie was proposed. This algorithm adopted recursive hash function to store the patterns in bit-vectors in place of the state transition table in order to reduce space consumption. Further more it made use of the rank operation for fast verification. Theoretic analysis shows that the space complexity of HashTrie is O(|P|), which is linear with the size of pattern set |P| and is independent of the alphabetsize sigma. The space complexity is superior to the complexity O(|P|sigmal log|P|) of AC. Experiments on synthetic datasets and real-world datasets (such as Snort, ClamAV and URL) show that HashTrie saves up to 99.6% storage cost compared with AC, and in the meanwhile it runs at a matching speed that is about half of AC. HashTrie is a space-efficient multiple s