Paper
20 October 2023 Protocol consistency vulnerability detection of UAV wireless communication network in power transmission and transformation project based on improved genetic algorithm
Shengchao Jiang, Bin Wang, Haoze Zhuo, Tailin Li, Zecheng Lv
Author Affiliations +
Proceedings Volume 12814, Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023); 1281402 (2023) https://doi.org/10.1117/12.3010243
Event: Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023), 2023, Chongqing, China
Abstract
The drone wireless communication network protocol is susceptible to the influence of URL (Unified Resource Locator) encoding conditions, resulting in a low vulnerability detection rate. Therefore, it is necessary to design a new protocol consistency vulnerability detection method for unmanned aerial vehicle wireless communication network based on improved genetic algorithm in power transmission and transformation engineering. A drone wireless communication network consistency vulnerability detection environment was configured, and an improved genetic algorithm was used to generate a protocol consistency vulnerability detection objective function for the wireless communication network. The objective function was solved and consistency vulnerability detection was completed. The experimental results show that this method has a high vulnerability detection rate, good detection effect, reliability, and certain application value in power transmission and transformation engineering.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Shengchao Jiang, Bin Wang, Haoze Zhuo, Tailin Li, and Zecheng Lv "Protocol consistency vulnerability detection of UAV wireless communication network in power transmission and transformation project based on improved genetic algorithm", Proc. SPIE 12814, Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023), 1281402 (20 October 2023); https://doi.org/10.1117/12.3010243
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KEYWORDS
Wireless communications

Unmanned aerial vehicles

Wireless energy transfer

Genetic algorithms

Head

Engineering

Environmental sensing

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