Detection of flooding attacks on mobile agents using sketch technique and divergence measures

This paper deals with detection of SYN flooding attacks which are the most common type of attacks in a Mobile Agent World. We propose a new framework for the detection of flooding attacks by integrating Divergence measures over Sketch data structure. The performance of the proposed framework is investigated in terms of detection probability and false alarm ratio. We focus on tuning the parameter of Divergence Measures to optimize the performance. We will evaluate the performance of the proposed divergence measure via the receiver operating characteristic. Our analysis results prove that our proposed algorithm outperforms the existing solutions.