A machine learning-based trust evaluation model for wireless sensor networks

被引：0

作者：

Huang, Yiyang ^{[1
]}

Li, Xiaoyong ^{[1
]}

Yuan, Jie ^{[1
]}

Yuan, Kaiguo ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, Key Lab Trustworthy Distributed Comp & Serv, Beijing 100876, Peoples R China

来源：

PROCEEDINGS OF 2024 3RD INTERNATIONAL CONFERENCE ON CYBER SECURITY, ARTIFICIAL INTELLIGENCE AND DIGITAL ECONOMY, CSAIDE 2024 | 2024年

关键词：

Computational trust; Feature extraction; Model classification; WSN; MANAGEMENT;

D O I：

10.1145/3672919.3673035

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Wireless sensor networks have been widely used in many industries, where sensor nodes are used to perform specific tasks, such as information collection or data transmission. Due to the particularity of sensor nodes, the trust mechanism of their nodes has been difficult to establish. Different from the traditional trust evaluation model, this paper proposes a trust evaluation model based on machine learning principles. By combining the extracted trust features, the final trust value is obtained for decision-making. Experimental results show that the model is effective and has higher accuracy than other methods.

引用

页码：654 / 658

页数：5

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