Energy Efficient Defense Against Cooperative Hostile Detection and Eavesdropping Attacks for AAV-Aided Short-Packet Transmissions

Autonomous aerial vehicle (AAV)-aided short-packet transmissions have emerged as a promising paradigm for supporting mission-critical applications in future mobile communication networks. However, the security issues raised by the open nature of the wireless transmission deserve attention, especially when confronted with cooperative wardens and eavesdroppers. To this end, we consider a new framework for an energy-efficient design of AAV-aided short-packet transmission systems against cooperative hostile detection and eavesdropping attacks. Specifically, the false rate of the cooperative hostile detection is first derived by utilizing the likelihood ratio test and the bivariate Gaussian distribution property. Then, we formulate a problem to maximize the minimum covert secrecy energy efficiency (MCSEE) by jointly optimizing the user association, AAV power control, and AAV three-dimensional (3D) trajectory design. We propose a penalty-based dual-loop iterative optimization algorithm to tackle this complex problem suboptimally with the aid of auxiliary penalty variables, where the communication resource scheduling, the AAV trajectory planning, and the auxiliary penalty variables are optimized in the inner loop. In particular, the intractable joint AAV power control and 3D trajectory design sub-problem is suboptimally addressed by introducing slack variables and employing successive convex approximation (SCA) techniques. The penalty factor is updated in the outer loop. Finally, numerical results are provided to verify the effectiveness and superiority of our proposed solution to several benchmarks.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2024-10-18
DOI
https://doi.org/10.1109/tvt.2024.3483256
Citations
8
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
10.39

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article

Energy Efficient Defense Against Cooperative Hostile Detection and Eavesdropping Attacks for AAV-Aided Short-Packet Transmissions

Haobin Mao, Zhenyu Xiao, Zhu Han, Xiang‐Gen Xia et al.
8 citations
IEEE Transactions on Vehicular Technology
UAV Applications and Optimization
10.39
article

Energy Efficient Defense Against Cooperative Hostile Detection and Eavesdropping Attacks for AAV-Aided Short-Packet Transmissions

Haobin Mao, Zhenyu Xiao, Zhu Han, Xiang‐Gen Xia, Yanming Liu
article en
8 citations

Abstract

Autonomous aerial vehicle (AAV)-aided short-packet transmissions have emerged as a promising paradigm for supporting mission-critical applications in future mobile communication networks. However, the security issues raised by the open nature of the wireless transmission deserve attention, especially when confronted with cooperative wardens and eavesdroppers. To this end, we consider a new framework for an energy-efficient design of AAV-aided short-packet transmission systems against cooperative hostile detection and eavesdropping attacks. Specifically, the false rate of the cooperative hostile detection is first derived by utilizing the likelihood ratio test and the bivariate Gaussian distribution property. Then, we formulate a problem to maximize the minimum covert secrecy energy efficiency (MCSEE) by jointly optimizing the user association, AAV power control, and AAV three-dimensional (3D) trajectory design. We propose a penalty-based dual-loop iterative optimization algorithm to tackle this complex problem suboptimally with the aid of auxiliary penalty variables, where the communication resource scheduling, the AAV trajectory planning, and the auxiliary penalty variables are optimized in the inner loop. In particular, the intractable joint AAV power control and 3D trajectory design sub-problem is suboptimally addressed by introducing slack variables and employing successive convex approximation (SCA) techniques. The penalty factor is updated in the outer loop. Finally, numerical results are provided to verify the effectiveness and superiority of our proposed solution to several benchmarks.

IEEE Transactions on Vehicular TechnologyVol. 74(2)
University of Houston (US), Beihang University (CN), University of Delaware (US)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Affordable and clean energy
Openalex Percentile: Top 2%
UAV Applications and Optimization
10.39
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