FPGA-BASED NEURO-ARCHITECTURE THAT CAN DETECT NOVEL ATTACKS

Electronics and Comm. Eng. Dept., Faculty of Eng., Mansoura University

Intrusion Detection Systems (IDSs) have emerged as one of the most promising ways of providing

security in computer networks. Software neural-network-based techniques for implementing IDS have

been proved to be capable of learning and recognizing attacks it faces for the first time. Hardware,

particularly FPGA-based, implementation techniques provide much higher performance over software

techniques through its highly parallel architectures. This paper proposes a software neuro-based system

that can detect novel attacks. In addition, this work also introduces the applicability of using FPGA

devices to enhance the performance of software neuro-based systems. An FPGA-based architecture

was optimized to meet the requirements of speed and area such that it can not only enhance the speed,

but also it can provide an improved scope of boosting security over the software-based system.