Payam Mahdinia - Student of Master of Science of Computer Architecture, Isfahan University of Technology
Mehdi Berenjkoob - Assistant Professor of Electrical and Computer Engineering, Isfahan University of Technology
Hedayat Vatankhah - Master of Science of Artificial Intelligence, Payampardaz Engineering Co

Network Intrusion Detection Systems (NIDS) which should perform time-consuming evaluation of every packet received from network have faced throughput challenge as aresult of the increase in the speed of network communications and the high volume of Internet threats. In an NIDS, the mostimportant and time-consuming processes are pattern matching and deep inspection of the header and the body of packets. Several analyses show that this process can take upto 75% of the time of processing packets. In this paper, relying on the processing power of general purpose graphicscards – which seem to be a better option compared to other hardware technologies like FPGAs with regard to speed, scalability, flexibility, ease of programming and price – and with the idea of having the signature-based detection engine of NIDS systems run on GPU rather than CPU, it is tried topresent an efficient method to increase the speed of intrusion detection systems such as Snort. The proposed methodprovides a means to perform payload matching and nonpayloadmatching of packets in a parallel platform on GPU, which can speed up the signature-based detection engine of Snort 3.6.

Network Intrusion Detection Systems, Attack Signatures, Pattern Matching, Graphics Card,Throughput