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Fast and Scalable Pattern Matching for Network Intrusion Detection Systems

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2 Author(s)
S. Dharmapurikar ; Dept. of Comput. Sci. & Eng., Washington Univ., St. Louis, MO ; J. W. Lockwood

High-speed packet content inspection and filtering devices rely on a fast multipattern matching algorithm which is used to detect predefined keywords or signatures in the packets. Multipattern matching is known to require intensive memory accesses and is often a performance bottleneck. Hence, specialized hardware-accelerated algorithms are required for line-speed packet processing. We present hardware-implementable pattern matching algorithm for content filtering applications, which is scalable in terms of speed, the number of patterns and the pattern length. Our algorithm is based on a memory efficient multihashing data structure called Bloom filter. We use embedded on-chip memory blocks in field programmable gate array/very large scale integration chips to construct Bloom filters which can suppress a large fraction of memory accesses and speed up string matching. Based on this concept, we first present a simple algorithm which can scan for several thousand short (up to 16 bytes) patterns at multigigabit per second speeds with a moderately small amount of embedded memory and a few mega bytes of external memory. Furthermore, we modify this algorithm to be able to handle arbitrarily large strings at the cost of a little more on-chip memory. We demonstrate the merit of our algorithm through theoretical analysis and simulations performed on Snort's string set

Published in:

IEEE Journal on Selected Areas in Communications  (Volume:24 ,  Issue: 10 )