In this paper, we propose a secure unmanned aerial vehicle (UAV) mobile edge computing (MEC) system where multiple ground users offload large computing tasks to a nearby legitimate UAV in the presence of multiple eavesdropping UAVs with imperfect locations. To enhance security, jamming signals are transmitted from both the full-duplex legitimate UAV and non-offloading ground users. For this system, we design a low-complexity iterative algorithm to maximize the minimum secrecy capacity subject to latency, minimum offloading and total power constraints. Specifically, we jointly optimize the UAV location, users’ transmit power, UAV jamming power, offloading ratio, UAV computing capacity, and offloading user association. Numerical results show that our proposed algorithm significantly outperforms baseline strategies over a wide range of UAV self-interference (SI) efficiencies, locations and packet sizes of ground users. Furthermore, we show that there exists a fundamental tradeoff between the security and latency of UAV-enabled MEC systems which depends on the UAV SI efficiency and total UAV power constraints.

中文翻译：

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支持无人机的移动边缘计算系统的安全通信

在本文中，我们提出了一种安全的无人机 (UAV) 移动边缘计算 (MEC) 系统，在存在多个位置不完美的窃听无人机的情况下，多个地面用户将大型计算任务卸载到附近的合法无人机上。为了增强安全性，干扰信号从全双工合法无人机和非卸载地面用户传输。对于这个系统，我们设计了一种低复杂度的迭代算法，以最大化受延迟、最小卸载和总功率限制的最小保密容量。具体来说，我们联合优化了无人机位置、用户发射功率、无人机干扰功率、卸载比、无人机计算能力和卸载用户关联。数值结果表明，我们提出的算法在地面用户的各种无人机自干扰 (SI) 效率、位置和数据包大小方面明显优于基线策略。此外，我们表明，在启用 UAV 的 MEC 系统的安全性和延迟之间存在基本权衡，这取决于 UAV SI 效率和 UAV 总功率限制。