الفهرس 
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Abstract
With the rapid expansion of computer networks and its services durin
the past decade, network security has become a very important issue. Currently, intrusion detection systems (IDSs) are playing an essential part of any network security system. A challenging task in designing such IDSs is the ability of detecting the system attacks at a high speed and with an acceptable accuracy to minimize any possible damage.
In this work, an IDS system is proposed and designed with two keys of success; its neuro-architecture, and the FPGA-based implementation of this architecture. The neuro-architecture provides the potential to identify and classify known attacks as well as novel attacks. In addition, the proposed system has fast decision due to the natural parallelism propriety of the neural networks. Also, the software implementation of the proposed system is explained. Furthermore, an FPGA-based implementation of the. system is realized to provide an extra enhancement of system speed and to add an improved scope of boosting security over the software-based system.