Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院

Journal:Comput Electr Eng

Abstract:IoT devices have become much popular in our daily lives, while attackers often invade network nodes to launch various attacks. In this work, we focus on the detection of insider attacks in IoT networks. Most existing algorithms calculate the reputation of all nodes based on the routing path. However, they rely heavily on the assumption that different nodes in the same routing path have equal reputation, which may be not invalid in practice and cause inaccurate detection results. To solve this issue, we formulate it as a multivariate multiple linear regression problem and use the K-means classification algorithm to detect malicious nodes. Further, we optimize the routing path and design an enhanced detection scheme. Our results indicate that our proposed methods could achieve a detection accuracy rate of 90% or above in a common case, and the enhanced scheme could reach an even lower false detection rate, i.e., below 5%. © 2019 Elsevier Ltd

ISSN No.:0045-7906

Translation or Not:no

Date of Publication:2019-07-01

Co-author:Yang, Jingxiu,Meng, Weizhi

Correspondence Author:Liu Liang