NFA based regular expression matching on FPGA

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2018

Öğrenci: KAMİL SERT

Danışman: CÜNEYT FEHMİ BAZLAMAÇCI

Özet:

String matching is about finding all occurrences of a string within a given text, which is a classical but still a popular problem. String matching algorithms have important roles in various real world areas, such as web and security applications. In this work, we are interested in solving regular expression and hence string matching problem targeting especially the network intrusion detection systems (NIDS) field. An NIDS engine inspects both the header and the content of the packet and hence performs a type of deep packet inspection also. This inspection requires effective string matching techniques because each network packet should be checked and compared against maybe hundreds of possible malicious attacks at line speed. In this thesis, a detailed literature analysis is presented first that explains and classifies regular expression matching studies. Among these, studies exist that presents nondeterministic finite automata (NFA) based architectures and their novel mappings onto FPGA. In our study we select one such study [1] and further modify vi and enhance the NFA architecture already proposed. The reference study uses the modified-McNaughton-Yamada-algorithm and maps the resulting NFA into structural HDL for FPGA implementation. Our modification proposes to use a 2-character based matching structure that yields better memory utilization. With our approach, the circuit for the NFA representation needs less number of states (hence flip-flops) and LUTs to perform the 2-character regular expression matching process. Within the scope of this thesis, an extensive evaluation study is performed using the well-known Snort IDS ruleset and the worst case evaluation is done using some intuitively and synthetically created regular expressions targeting Xilinx 7-series FPGAs. Evaluation results are obtained using various performance metrics.