Detection Technology for Hostile Attacks to Campus Wireless Network

Abstract

The detection technology for malicious attacks to campus wireless network is analyzed. In this paper, a detection method based on PrefixSpan algorithm for malicious attacks to campus wireless network is adopted. Aiming at hostile attacks environment to the wireless network campus, the detection method is proposed to reduce the amount of computation and memory consumption, and through incremental learning to achieve training of large data, and improve performance of mining further. Experimental results show that the proposed algorithm for hostile attacks detection to campus wireless network, can effectively improve accuracy and security of detection, and achieved the desired results.