User abnormal behaviour sequence detection method based on Markov chain and SVDD

2019 3rd International Workshop on Renewable Energy and Development

能源学;生态环境科学

Zou, Shengyuan^1 ; Chang, Chaowen^1 ; Han, Peisheng^1

Information Engineering University, Zhengzhou, Henan

450001, China^1

关键词: Abnormal behaviours;    Anomaly detection methods;    Detection efficiency;    Sequence detection;    Sequence informations;    Sequence modeling;    Support vector data;    User behaviour;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/267/4/042061/pdf
DOI  :  10.1088/1755-1315/267/4/042061

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

In order to solve the problem of insufficient use of sequence information and low detection efficiency of traditional anomaly detection methods, this paper introduces Markov chain into user behaviour sequence detection, and proposes a description based on Markov chain and support vector data field ( SVDD) User Behaviour Sequence Detection Method (ASDMS), which first uses the Markov chain to accurately quantify the user behaviour sequence, then constructs the user's normal behaviour sequence model based on the support vector data field description model, and identifies the user anomaly behaviour. The experimental results show that the ASDMS method has better performance and timeliness than the traditional abnormal behaviour detection method.