Against Mobile Collusive Eavesdroppers: Cooperative Secure Transmission and Computation in UAV-Assisted MEC Networks

IF 7.7 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Mingxiong Zhao;Zirui Wang;Kun Guo;Rongqian Zhang;Tony Q. S. Quek
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引用次数: 0

Abstract

In Uncrewed Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) networks, the security of transmission faces significant challenges due to the vulnerabilities of line-of-sight links and potential eavesdropping on two-hop links. This paper addresses these challenges with an innovative Cooperative Secure Transmission and Computation strategy (CSTC), specifically engineered for time-slotted UAV-assisted MEC networks plagued by mobile collusive eavesdroppers. These eavesdroppers significantly bolster their interception capabilities through coordinated and optimized movements, escalating the security threats. To neutralize these risks, the proposed CSTC employs the UAV and remote devices as helper nodes to emit jamming signals, thereby thwarting eavesdropping activities, while simultaneously facilitating the efficient relay of users’ tasks to the base station for advanced processing. The CSTC aims to maximize the sum Secrecy Transmission Rate (STR) satisfying task latency constraints. It involves a joint optimization of UAV trajectory, jamming beamformers, transmit power, and data offloading strategy to expedite task transmission. Additionally, a real-time computation scheduling approach is developed based on a newly defined metric, the Urgency Degree of Users (UDoU), to enhance task processing efficiency. Our extensive simulations validate that the CSTC not only elevates the sum STR but also consistently meets latency constraints, demonstrating its robustness against advanced mobile eavesdropping techniques.
针对移动合谋窃听者:无人机辅助MEC网络的协同安全传输与计算
在无人机(UAV)辅助的移动边缘计算(MEC)网络中,由于视距链路的漏洞和两跳链路的潜在窃听,传输的安全性面临重大挑战。本文通过创新的合作安全传输和计算策略(CSTC)解决了这些挑战,该策略专门针对受移动合谋窃听者困扰的时隙无人机辅助MEC网络而设计。这些窃听者通过协调和优化的行动大大增强了他们的拦截能力,升级了安全威胁。为了消除这些风险,本文提出的CSTC采用无人机和远程设备作为辅助节点发射干扰信号,从而阻止窃听活动,同时便于将用户的任务高效中继到基站进行高级处理。CSTC的目标是在满足任务延迟约束的情况下,使总保密传输速率(STR)最大化。它涉及无人机轨迹、干扰波束形成器、发射功率和数据卸载策略的联合优化,以加快任务传输。此外,为了提高任务处理效率,提出了一种基于用户紧急度(UDoU)的实时计算调度方法。我们的大量仿真验证了CSTC不仅提高了总STR,而且始终满足延迟约束,证明了其对高级移动窃听技术的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Mobile Computing
IEEE Transactions on Mobile Computing 工程技术-电信学
CiteScore
12.90
自引率
2.50%
发文量
403
审稿时长
6.6 months
期刊介绍: IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.
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