Abstract

In order to effectively solve the current security problems encountered by smart wireless terminals in the digital twin biological network, to ensure the stable and efficient operation of the wireless communication network. This research aims to reduce the interference attack in the communication network, an interference source location scheme based on Mobile Tracker in the communication process of the Internet of Things (IoT) is designed. Firstly, this paper improves Attribute-Based Encryption (ABE) to meet the security and overhead requirements of digital twin networking communication. The access control policy is used to encrypt a random key, and the symmetric encryption scheme is used to hide the key. In addition, in the proposed interference source location technology, the influence of observation noise is reduced based on the principle of unscented Kalman filter, and the estimated interference source location is modified by the interference source motion model. In order to further evaluate the performance of the method proposed as the interference source, this paper simulates the jamming attack scenario. The Root Mean Square Error (RMSE) value of the proposed algorithm is 0.245 ​m, which is better than the ErrMin algorithm (0.313 ​m), and the number of observation nodes of the proposed algorithm is less than half of the ErrMin algorithm. To sum up, satisfactory results can be achieved by taking the Jamming Signal Strength (JSS) information as the observation value and estimating the location of the interference source and other state information based on the untracked Kalman filter algorithm. This research has significant value for the secure communication of the digital twins in the IoT.

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