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刘亮

副教授 硕士生导师

招生学科专业:
软件工程 -- 【招收硕士研究生】 -- 计算机科学与技术学院
网络空间安全 -- 【招收硕士研究生】 -- 计算机科学与技术学院
电子信息 -- 【招收硕士研究生】 -- 计算机科学与技术学院

性别:男

学历:南京航空航天大学

学位:工学博士学位

所在单位:计算机科学与技术学院/人工智能学院/软件学院

联系方式:liangliu@nuaa.edu.cn

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Detection of multiple-mix-attack malicious nodes using perceptron-based trust in IoT networks

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所属单位:计算机科学与技术学院/人工智能学院/软件学院

发表刊物:Future Gener Comput Syst

摘要:The Internet of Things (IoT) has experienced a rapid growth in the last few years allowing different Internet-enabled devices to interact with each other in various environments. Due to the distributed nature, IoT networks are vulnerable to various threats especially insider attacks. There is a significant need to detect malicious nodes timely. Intuitively, large damage would be caused in IoT networks if attackers conduct a set of attacks collaboratively and simultaneously. In this work, we investigate this issue and first formalize a multiple-mix-attack model. Then, we propose an approach called Perceptron Detection (PD), which uses both perceptron and K-means method to compute IoT nodes’ trust values and detect malicious nodes accordingly. To further improve the detection accuracy, we optimize the route of network and design an enhanced perceptron learning process, named Perceptron Detection with enhancement (PDE). The experimental results demonstrate that PD and PDE can detect malicious nodes with a higher accuracy rate as compared with similar methods, i.e., improving the detection accuracy of malicious nodes by around 20% to 30%. © 2019 Elsevier B.V.

ISSN号:0167-739X

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发表时间:2019-12-01

合写作者:Ma, Zuchao,Meng, Weizhi

通讯作者:Ma, Zuchao,刘亮

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