2005Unpublished venueRequires access

A pattern matching co-processor for network security

Y.H. Cho, William H. Mangione-Smith

Open publisher page 35 citations

Abstract

It has been estimated that computer network worms and virus caused the loss of over $55B in 2003. Network security system use techniques such as deep packet inspection to detect the harmful packets. While software intrusion detection system running on general purpose processors can be updated in response to new attacks. They lack the processing power to monitor gigabit networks. We present a high performance pattern matching co-processor architecture that can be used to monitor and identify a large number of intrusion signature. The design consists of a bank of pattern matchers that are used to implement a highly concurrent filter. The pattern matchers can be programmed to match multiple patterns of various lengths, and are able to leverage the existing databases of threat signatures. We have been able to program the filters to match all the payload patterns defined in the widely used Snort network intrusion detection system at a rate above 7 Gbps, with memory space left to accommodate threat signatures that become available in the future.

About this research paper

What this paper is about

It has been estimated that computer network worms and virus caused the loss of over $55B in 2003. Network security system use techniques such as deep packet inspection to detect the harmful packets. While software intrusion detection system running on general purpose processors can be updated in response to new attacks. They lack the processing power to monitor gigabit networks. We present a high performance pattern matching co-processor architecture that can be used to monitor and identify a large number of intrusion signature. The design consists of a bank of pattern matchers that are used to implement a highly concurrent filter. The pattern matchers can be programmed to match multiple patterns of various lengths, and are able to leverage the existing databases of threat signatures. We have been able to program the filters to match all the payload patterns defined in the widely used Snort network intrusion detection system at a rate above 7 Gbps, with memory space left to accommodate threat signatures that become available in the future.

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OpenAlex reports 35 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

It has been estimated that computer network worms and virus caused the loss of over $55B in 2003. Network security system use techniques such as deep packet inspection to detect the harmful packets. While software intrusion detection system running on general purpose processors can be updated in response to new attacks. They lack the processing power to monitor gigabit networks. We present a high performance pattern matching co-processor architecture that can be used to monitor and identify a large number of intrusion signature. The design consists of a bank of pattern matchers that are used to implement a highly concurrent filter. The pattern matchers can be programmed to match multiple patterns of various lengths, and are able to leverage the existing databases of threat signatures. We have been able to program the filters to match all the payload patterns defined in the widely used Snort network intrusion detection system at a rate above 7 Gbps, with memory space left to accommodate threat signatures that become available in the future.

Key concepts: Computer science, Network processor, Intrusion detection system, Network packet, Payload (computing), Pattern matching, Embedded system, Leverage (statistics)

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