An Active Defense Adjudication Method Based on Adaptive Anomaly Sensing for Mimic IoT

Sisi Shao, Tiansheng Gu, Yijun Nie, Zongkai Ji, Fei Wu, Zhongjie Ba, Yimu Ji, Kui Ren, Guozi Sun

Abstract: Security issues in the Internet of Things (IoT) are inevitable. Uncertain threats, such as known vulnerabilities and backdoors exist within IoT, and traditional passive network security technologies are ineffective against uncertain threats. To address the above issues, we propose an active defense adjudication method based on adaptive anomaly sensing for mimic IoT. The method constructs a mimic IoT active defense architecture, improving system security and reliability despite prevailing security threats. In addition, an intelligent anomaly sensing algorithm is integrated into the adjudication module of the mimic IoT active defense architecture to support arbitration. An adaptive anomaly sensing model based on multi-feature selection is used to determine the anomaly score of the IoT device outputs, and this model fully considers the reliability of the adjudication data and improves the accuracy of the adjudication. Finally, we conduct a comparative analysis of the proposed adjudication algorithm against three others via a mimic power communication IoT system as an application scenario. The experimental results show that our algorithm can improve security and reduce the failure rate of the mimic IoT system.

External IDs:dblp:journals/tsc/ShaoGNJWBJRS25