- Title
- Parallel packet classification using GPU co-processors
- Creator
- Nottingham, Alistair, Irwin, Barry V W
- Subject
- To be catalogued
- Date
- 2010
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/430250
- Identifier
- vital:72677
- Identifier
- https://doi.org/10.1145/1899503.1899529
- Description
- In the domain of network security, packet filtering for classification pur-poses is of significant interest. Packet classification provides a mecha-nism for understanding the composition of packet streams arriving at distinct network interfaces, and is useful in diagnosing threats and un-covering vulnerabilities so as to maximise data integrity and system se-curity. Traditional packet classifiers, such as PCAP, have utilised Con-trol Flow Graphs (CFGs) in representing filter sets, due to both their amenability to optimisation, and their inherent structural applicability to the metaphor of decision-based classification. Unfortunately, CFGs do not map well to cooperative processing implementations, and single-threaded CPU-based implementations have proven too slow for real-time classification against multiple arbitrary filters on next generation networks. In this paper, we consider a novel multithreaded classification algorithm, optimised for execution on GPU co-processors, intended to accelerate classification throughput and maximise processing efficien-cy in a highly parallel execution context.
- Format
- 9 pages, pdf
- Language
- English
- Relation
- Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists, Nottingham, A. and Irwin, B., 2010, October. Parallel packet classification using GPU co-processors. In Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists (pp. 231-241), Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists volume 2010 number 1 231 241 2010 978-1-60558-950-3
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the ACM Digital Library Statement (https://libraries.acm.org/digital-library/policies#anchor3)
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- Visitors: 17
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Collections
Irwin, Barry V W (Prof)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
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