According to the problems of current distributed architecture intrusion detection systems (DIDS), a new online distributed\nintrusion detection model based on cellular neural network (CNN) was proposed, in which discrete-time CNN (DTCNN) was\nused as weak classifier in each local node and state-controlled CNN (SCCNN) was used as global detection method, respectively.\nWe further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental\nresults based on KDDCUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach\nis affordable to parallelism and analog very large scale integration (VLSI) implementation which allows the distributed intrusion\ndetection to be performed better.
Loading....