Title | ||
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Multiple pattern matching for network security applications: Acceleration through vectorization |
Abstract | ||
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As both new network attacks emerge and network traffic increases in volume, the need to perform network traffic inspection at high rates is ever increasing. The core of many security applications that inspect network traffic (such as Network Intrusion Detection) is pattern matching. At the same time, pattern matching is a major performance bottleneck for those applications: indeed, it is shown to contribute to more than 70% of the total running time of Intrusion Detection Systems. Although numerous efficient approaches to this problem have been proposed on custom hardware, it is challenging for pattern matching algorithms to gain benefit from the advances in commodity hardware. This becomes even more relevant with the adoption of Network Function Virtualization, that moves network services, such as Network Intrusion Detection, to the cloud, where scaling on commodity hardware is key for performance. |
Year | DOI | Venue |
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2020 | 10.1016/j.jpdc.2019.10.011 | Journal of Parallel and Distributed Computing |
Keywords | Field | DocType |
Pattern matching,SIMD,Vectorization,Gather | Algorithm design,Computer science,Network security,Vectorization (mathematics),Data parallelism,Pattern matching,Intrusion detection system,Speedup,Distributed computing,Scalability | Journal |
Volume | ISSN | Citations |
137 | 0743-7315 | 2 |
PageRank | References | Authors |
0.37 | 19 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Charalampos Stylianopoulos | 1 | 3 | 2.42 |
Magnus Almgren | 2 | 270 | 39.17 |
Olaf Landsiedel | 3 | 562 | 43.33 |
Marina Papatriantafilou | 4 | 316 | 45.72 |