Security Clustering Algorithm Based on Integrated Trust Value for Unmanned Aerial Vehicles Network

• Jingxian Zhou,
• Zengqi Wang,

Vol. 14, No. 4, April 30, 2020
10.3837/tiis.2020.04.020, Download Paper (Free):

• UAVs network
• clustering algorithm
• cluster head selection
• Bayesian trust model
• network security.

Abstract

Unmanned aerial vehicles (UAVs) network are a very vibrant research area nowadays. They have many military and civil applications. Limited bandwidth, the high mobility and secure communication of micro UAVs represent their three main problems. In this paper, we try to address these problems by means of secure clustering, and a security clustering algorithm based on integrated trust value for UAVs network is proposed. First, an improved the k-means++ algorithm is presented to determine the optimal number of clusters by the network bandwidth parameter, which ensures the optimal use of network bandwidth. Second, we considered variables representing the link expiration time to improve node clustering, and used the integrated trust value to rapidly detect malicious nodes and establish a head list. Node clustering reduce impact of high mobility and head list enhance the security of clustering algorithm. Finally, combined the remaining energy ratio, relative mobility, and the relative degrees of the nodes to select the best cluster head. The results of a simulation showed that the proposed clustering algorithm incurred a smaller computational load and higher network security.

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