Evaluating Host-based Anomaly Detection Systems: Application of the One-class SVM Algorithm to ADFA-LD

摘要：

　　ADFA-LD is a recently released data set for evaluating host-based anomaly detection systems,aiming to substitute the existing benchmark data sets which have failed to reflect the characteristics of modern computer systems.In a previous work,we had attempted to evaluate ADFA-LD with a highly efficient frequency model but the performance is inferior.In this paper,we focus on the other typical technical category that detects anomalies with a short sequence model.In collaboration with the one-class SVM algorithm,a novel anomaly detection system is proposed for ADFA-LD.The numerical experiments demonstrate that it can not only achieve a satisfactory performance,but also reduce the computational cost largely.

作者: Miao Xie Jiankun Hu Jill Slay

作者单位: School of Engineering and Information Technology University of New South Wales at the Australian Defence Force Academy Canberra, Australia

会议类型: 国际会议

会议名称: The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

会议地点: 厦门

会议语种:英文

页码: 990-994

在线出版日期: 2014-08-19（万方平台首次上网日期，不代表论文的发表时间）