An Anomaly Detection Method Based on Session
Zeng Yong-zhon · Computer Technology and Development · 2014
With the development of network technology,the dependence of the network is more and more strong,but simultaneously the network attack cause serious leak of information and huge economic losses. How to find out the attacker from vast user access information is an important issue needs to be solved for Web service administrator. After the deep analysis of Web service log,find that there are different in character between abnormal and normal access users. By feature extracting and making some necessary assumptions,build anomaly detection model using Nave Bayesian classifier with a good detection effect.