Abstract
The current data anti-jamming methods lack the feature classification process, which leads to poor anti-jamming effect. In order to solve this problem, this paper proposes a data anti-jamming method based on machine learning algorithm for ad hoc networks. First of all, based on machine learning algorithm, the data transmitted in the ad hoc network is processed by feature mining and classification, and the ad hoc network information transmission management platform is constructed. Then optimize the steps of extracting the anti-jamming information features of the ad hoc network data, and combine machine learning algorithm to optimize the anti-jamming evaluation algorithm of the communication data of the internet of things, so as to achieve the identification and protection of the ad hoc network interference data. The experimental results show that this method has high practicability and can meet the research requirements.
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© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhang, Y., Ma, L. (2024). Data Anti-jamming Method for Ad Hoc Networks Based on Machine Learning Algorithm. In: Wang, B., Hu, Z., Jiang, X., Zhang, YD. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 534. Springer, Cham. https://doi.org/10.1007/978-3-031-50577-5_18
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DOI: https://doi.org/10.1007/978-3-031-50577-5_18
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