Visible to the public An FPGA Coarse Grained Intermediate Fabric for Regular Expression Search

TitleAn FPGA Coarse Grained Intermediate Fabric for Regular Expression Search
Publication TypeConference Paper
Year of Publication2017
AuthorsLuinaud, Thomas, Savaria, Yvon, Langlois, J.M. Pierre
Conference NameProceedings of the on Great Lakes Symposium on VLSI 2017
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4972-7
Keywordsdeep packet inspection, FPGA, IDS, overlay, pubcrawl, regular expression, resilience, Resiliency, Scalability
Abstract

Deep Packet Inspection systems such as Snort and Bro express complex rules with regular expressions. In Snort, the search of a regular expression is performed with a Non-deterministic Finite Automaton (NFA). Traversing an NFA sequentially with a CPU is not deterministic in time, and it can be very time consuming. The sequential traversal of an NFA with a CPU is not deterministic in time consequently it can be time consuming. A fully parallel NFA implemented in hardware can search all rules, but most of the time only a small part is active. Furthermore, a string filter determines the traversal of an NFA. This paper proposes an FPGA Intermediate Fabric that can efficiently search regular expressions. The architecture is configured for a specific NFA based on a partial match of a rule found by the string filter. It can thus support all rules from a set such as Snort, while significantly reduce compute resources and power con-sumption compared to a fully parallel implementation. Multiple parameters can be selected to find the best tradeoff between resource consumption and the number and types of supported expressions. This architecture was implemented on a Xilinx R XC7VX1140 Virtex-7. The reported implementation, can sustain up to 512 regular expressions, while requiring 2% of the slices and 16% of the BRAM resources, for a throughput of 200 million characters per second.

URLhttp://doi.acm.org/10.1145/3060403.3060429
DOI10.1145/3060403.3060429
Citation Keyluinaud_fpga_2017