An Intrusion Detection Scheme Based on Anomaly Mining in Internet of Things
Internet of things (IOT) is vulnerable to malicious attacks because of opening deployment and limited resources. It’s heterogeneous and distributed characters make conventional intrusion detection methodologies hard to deploy. To overcome this problem, this paper shows an intrusion detection scheme based on the anomaly mining. The paper has two parts – (I) in the first part an anomaly mining algorithm is developed to detect anomaly data of perception layer, (ii) in the second part a distributed intrusion detection scheme is designed based on the detected anomalies. Since not all anomalies are triggered by malicious intrusion, the intrusion semantic is analyzed to distinguish intrusion behaviors from anomalies. Finally our evaluation and analysis shows that our approach is accurate and extensible.
Internet of thins intrusion detection anomaly mining intrusion semantic description
Rongrong Fu Kangfeng Zheng Dongmei Zhang Yixian Yang
School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China In Information Security Center, Beijing University of Posts and Telecommunications, Beijing 100876, Chi School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China In
国际会议
北京
英文
315-320
2011-11-27（万方平台首次上网日期，不代表论文的发表时间）