Energy-Efficient Pipelined Bloom Filters for Network Intrusion Detection

Software-based detection techniques are commonly used to identify the predefined signatures in network streams. However, the software-based techniques can not keep up with the speeds that network bandwidth increases. Hence, hardware-based systems have started to emerge. Bloom filters are frequently used to identify malicious content like viruses in high speed networks. However, architectures proposed to implement Bloom filters are not power efficient. We propose a new Bloom filter architecture that exploits the well-known pipelining technique. Through extensive power analysis we show that pipelining can reduce the power consumption of Bloom filters up to 90 %, which leads to the energy-efficient implementation of network intrusion detection systems.