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Virus detection at the router level is rapidly gaining in importance. Hardware-based implementations have the advantage of speed and hence can support a large throughput. In this paper we describe an FPGA-based implementation of the Bloom filter virus detection code that is compiled from the native C to VHDL and mapped onto a Virtex XC2V8000 FPGA. Our results show that a single engine tailored for handling virus signatures of length eight bytes can achieve a throughput of 18.6 Gbps while occupying only 8% of the FPGA area. Studies on economic impact of computer viruses have shown that global businesses incurred an estimated $55 billion in damages during the year of 2003 (12). The report also estimates that the monetary losses due to viruses could further increase in the forthcoming years. Therefore, containing new virus outbreaks is one of the greatest challenges facing networks and organizations. One way to control virus outbreaks is to scan for viruses at the router/interconnection points. Packets generated from infected files contain signatures, which are strings that uniquely identify the presence of malicious code in an incoming packet. Signatures could be distributed anywhere within a packet or across packets. By accurately identifying signatures in incoming packets, malicious packets could be blocked at the router level, thereby making the networks more secure. Speed is the greatest concern while handling packets at the routers and hence, any router-level signature detection mechanism should be capable of identifying signatures accurately at high throughputs. This could be accomplished by a dedicated hardware (ASIC or FPGA) that inspects packets in parallel to detect signatures. Advances in high density FPGAs have provided designers with a viable commercial alternative to ASICs. Unlike ASICs, FPGAs do not require a prohibitively high cost of mask production. In this paper, we present ROCC, a C to native VHDL compiler framework. We demonstrate this tool by using it to generate hardware for Bloom-filter based virus detection. Our compiler framework can be easily adapted to accommodate new algorithms

Automatic Compilation Framework for Bloom Filter Based Intrusion Detection