2017/10/24 by Milan Češka, Vojtěch Havlena, Ceska, Milan +7
Computer Science · #Algorithms and Data Compression #FOS: Computer and information sciences #Formal Languages and Automata Theory (cs.FL) #Logic in Computer Science (cs.LO) #Network Packet Processing and Optimization #Network Security and Intrusion Detection #Networking and Internet Architecture (cs.NI)
paper · pdf · doi:10.48550/arxiv.1710.08647
openalex publication_date 2017/10/24 · openalex created_date 2018/04/13 · openalex updated_date 2026/07/28
We consider the problem of approximate reduction of non-deterministic automata that appear in hardware-accelerated network intrusion detection systems (NIDSes). We define an error distance of a reduced automaton from the original one as the probability of packets being incorrectly classified by the reduced automaton (wrt the probabilistic distribution of packets in the network traffic). We use this notion to design an approximate reduction procedure that achieves a great size reduction (much beyond the state-of-the-art language-preserving techniques) with a controlled and small error. We have implemented our approach and evaluated it on use cases from Snort, a popular NIDS. Our results provide experimental evidence that the method can be highly efficient in practice, allowing NIDSes to follow the rapid growth in the speed of networks.