Energy-Efficient Superconductor Bloom Filters for Streaming Data Inspection

摘要

Bloom filters can be used in network intrusion detection systems to detect known attack signatures in packet payloads. In this paper we propose and analyze the potential application of superconductor flux quantum technology for streaming data inspection with Bloom filters designed with Reciprocal Quantum Logic (RQL). This paper describes the gate-level design, performance, and energy-efficiency analysis of three superconductor 2 Kbit Bloom filters with 1) the run-time selection of the number of hashes per stream, and 2) different numbers of input streams per Bloom filter. The Bloom filter circuits were designed using a bottom-up approach with manual placing and routing of basic RQL gates. The design complexity is below 97K Josephson junctions. The highest clock frequency reached in the simulation of the circuits is 14.7 GHz. The false positive ra tes of the RQL Bloom filters are in very close agreement with the theoretical expectations of the false positive probability for the filters. For the cryocooling efficiency of 0.1 percent, the RQL Bloom filters demonstrate high energy efficiency in the range of similar to 1.5-43.6 pJ/stream/operation at room temperature for stream lengths from 16 to 256 bits. All circuits are designed and simulated for the 248 nm MIT Lincoln Laboratory SFQ5ee fabrication process.