High performance string matching algorithm for a network intrusion prevention system (NIPS)

Abstract

Intrusion detection systems (IDS) were developed to identify and report attacks in the late 1990s, as hacker attacks and network worms began to affect the Internet. Traditional IDS technologies detect hostile traffic and send alerts but do nothing to stop the attacks. Network intrusion prevention systems (NIPS) are deployed in-line with the network segment being protected. As the traffic passes through the NIPS, it is inspected for the presence of an attack. Like viruses, most intruder activities have some sort of signatures. Therefore, a pattern-matching algorithm resides at the heart of the NIPS. When an attack is identified, the NIPS blocks the offending data. There is an alleged trade-off between the accuracy of detection and algorithmic efficiency. Both are paramount in ensuring that legitimate traffic is not delayed or disrupted as it flows through the device. For this reason, the pattern-matching algorithm must be able to operate at wire speed, while simultaneously detecting the main bulk of intrusions. With networking speeds doubling every year, it is becoming increasingly difficult for software based solutions to keep up with the line rates. This paper presents a novel pattern-matching algorithm. The algorithm uses a ternary content addressable memory (TCAM) and is capable of matching multiple patterns in a single operation. The algorithm achieves line-rate speed of several orders of magnitude faster than current works, while attaining similar accuracy of detection. Furthermore, our system is fully compatible with Snort's rules syntax, which is the de facto standard for intrusion prevention systems