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| Content Provider | ACM Digital Library |
|---|---|
| Author | Boughzala, Bochra Langlois, J.M. Pierre Vakili, Shervin Savaria, Yvon |
| Abstract | The increasing complexity of cyber-attacks necessitates the design of more efficient hardware architectures for real-time Intrusion Detection Systems (IDSs). String matching is the main performance-demanding component of an IDS. An effective technique to design high-performance string matching engines is to partition the target set of strings into multiple subgroups and to use a parallel string matching hardware unit for each subgroup. This paper introduces a novel pattern grouping algorithm for heterogeneous bit-split string matching architectures. The proposed algorithm presents a reliable method to estimate the correlation between strings. The correlation factors are then used to find a preferred group for each string in a seed growing approach. Experimental results demonstrate that the proposed algorithm achieves an average of 41% reduction in memory consumption compared to the best existing approach found in the literature, while offering orders of magnitude faster execution time compared to an exhaustive search. |
| Starting Page | 37 |
| Ending Page | 42 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450341837 |
| DOI | 10.1145/2881025.2881031 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-03-17 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | String matching Computer network security Deep packet inspection Intrusion detection systems |
| Content Type | Text |
| Resource Type | Article |
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