QCF for deep packet inspection

Abstract

Deep packet inspection (DPI) acts as a tool to control and classify incoming network traffic depending on users,content, applications and becomes a very important aspect of every network today. Instead of utilising only incoming packet header information, Internet service providers utilise DPI for security purposes, flow management, and routing. The highperformance challenges that face DPI techniques to manage line-speed packet processing with restricted available memory are the increasing traffic volumes and link rates. Bloom (BF) and quotient (QF) filters are effective randomised data structures for performing approximate membership queries. They have been employed in many networking applications including DPI. Nevertheless, they consume more calculations which degrade the system performance. Consequently, in this paper, the authors propose a new variant of membership query data structure, called quotient-based Cuckoo filter (QCF), that reflects a merging process between QF and CF to minimise the calculation overhead and employing it in a DPI system. QCF employs only two hash functions and consumes less calculation overhead than BF, QF, and CF. The implementation results show that using QCF as an identification tool in a DPI system result in a time improvement up to 77% over CF and up to 98% over BF and QF.