FPGA-Based Network Traffic Security: Design and Implementation Using C5.0 Decision Tree Classifier

Abstract

In this work, a hardware intrusion detection system (IDS) model and its implementation are introduced to perform online real-time traffic monitoring and analysis. The introduced system gathers some advantages of many IDSs:hardware based from implementation point of view, network based from system type point of view, and anomaly detection from detection approach point of view. In addition, it can detect most of network attacks, such as denial of services (DoS), leakage, etc. from detection behavior point of view and can detect both internal and external intruders from intruder type point of view. Gathering these features in one IDS system gives lots of strengths and advantages of the work. The system is implemented by using field programmable gate array (FPGA), giving a more advantages to the system. A C5.0 decision tree classifier is used as inference engine to the system and gives a high detection ratio of 99.93%.