Abstract
As the concept of network evolves and diverge for ease of end-to-end communication in a real-time scenario, the unknown problems also rooted with that as a challenge for users. For instance, an advance method of attacking a network system to make it unusable for the legitimate user is called DDoS attack. DDoS attacks are an annoyance at a minimum, and if they are against a Critical Information Infrastructure(CII) networks or system, they can cause severe damage to network resources, say, service slowdown, communication failure between network users, financial loss and spoil good reputation. In order to protect CII, we developed detection mechanism for DoS and DDoS attacks using machine learning techniques. In this paper, we share our implementation methodology on different platforms (FPGA [1], x86 and PowerPC [2]). In addition, we compare the performance on different platforms using standard dataset(DARPA) and limited number of real time dataset.
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