Improved clustering algorithm based on high-speed network data stream

Abstract

With the continuous development of network technology, the attack has become the biggest threat to the stable operation of the network. Intrusion detection technology is a proactive safety protection measure which provides real-time monitoring of internal attacks, external attacks, and misuse. Traditional intrusion detection system is short of adaptability due to the complication and scale of the network. The main problem is that the real-time performance of the network is poor and the reliability is not high. This paper designs the intrusion detection mechanism combined with data stream clustering algorithm and intrusion detection system to solve the problem in processing a large amount of high-speed data streams. The performance of processing data streams is improved through the clustering algorithm based on density and the sliding window and the experiments show that the intrusion detection efficiency is higher than DenStream algorithm.