Secure NOMA-Based UAV-MEC Network Towards a Flying Eavesdropper

Lu, Weidang; Ding, Yu; Gao, Yuan; Chen, Yunfei; Zhao, Nan; Ding, Zhiguo; Nallanathan, Arumugam

doi:10.1109/tcomm.2022.3159703

Cited by 99 publications

(40 citation statements)

References 39 publications

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“…The authors show that the NOMA scheme outperforms its TDMA counterpart in terms of security capacity. A similar model is proposed by Lu et al [24]; a NOMAbased dual-UAV-MEC system with a flying service-provision UAV, a flying eavesdropping UAV, devices to be served, and a terrestrial jamming device. The authors formulate an optimization problem maximizing the average system security computation capacity by jointly optimizing SIC ordering variables, transmit powers, locally computed bits, UAV-MEC CPU frequency, and the service-providing UAV trajectory.…”

Section: Related Work and Novelty Of The Proposed Workmentioning

confidence: 99%

Design and Optimization of a UAV-Enabled Non-Orthogonal Multiple Access Edge Computing IoT System

Farha

Ismail

2022

IEEE Access

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Unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) in IoT systems has recently gained prominence as a solution to accommodate the low latency and high energy efficiency needs of emerging and developing 5G-and-beyond IoT applications. Given the limited spectrum available, non-orthogonal multiple access (NOMA) communication scheme provides a spectral-and power-efficient task offloading means. In this work, a novel framework is proposed for a multiple-UAV-enabled MEC IoT system incorporating uplink NOMA. The goal is to maximize the sum bits offloaded from all the IoT devices (IoTDs) in a finite service period. This is achieved through joint optimization of the associations between the IoTDs and the UAVs, the IoTD transmit powers, as well as the UAV trajectories, given UAV and IoTD energy budgets and quality-of-service (QoS) criteria. Towards that end, a specialized penalty block coordinate descent (P-BCD) algorithm is proposed to decompose the original problem into 4 subproblems that are solved alternately and iteratively. By direct comparison with several benchmark schemes including orthogonal multiple access (OMA), our proposed scheme displays performance enhancement in terms of sum bits offloaded and energy expenditure. Finally, a performance comparison is carried out for the proposed scheme with different number of employed UAVs to find the most cost-effective number of UAVs to deploy.INDEX TERMS Internet of Things (IoT), Mobile Edge Computing (MEC), Non-orthogonal multiple access (NOMA), Unmanned Aerial Vehicles (UAVs).

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Section: Related Work and Novelty Of The Proposed Workmentioning

confidence: 99%

Design and Optimization of a UAV-Enabled Non-Orthogonal Multiple Access Edge Computing IoT System

Farha

Ismail

2022

IEEE Access

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“…The main particularity in [78] is that NOMA was applied in a setup, where one UAV acted as a MEC node serving GSs, while a second UAV was a flying eavesdropper. Simultaneously, a ground jammer transmitted artificial noise to this eavesdropper.…”

Section: Noma Schemesmentioning

confidence: 99%

Secure UAV-Aided Mobile Edge Computing for IoT: A Review

et al. 2022

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As the Internet of Things (IoT) ecosystem evolves, innovative applications with stringent demands with respect to latency will emerge. To handle computation-intensive tasks in a timely manner, data offloading to Mobile Edge Computing (MEC) servers has been suggested. On the other hand, prospective IoT networks are expected to include Unmanned Aerial Vehicles (UAVs) to enhance coverage and connectivity, while retaining reliable communication links with ground nodes in urban, suburban, and rural terrain. Nevertheless, the evolution of UAV-aided MEC-enabled IoT presupposes the mitigation of security threats through the implementation of efficient and robust countermeasures. As UAVs inherently have certain limitations in terms of energy, computational, and memory resources, designing lightweight security solutions is required. This paper provides an overview of the UAV-aided MEC-enabled IoT and a detailed presentation of use cases and application scenarios, where security is of utmost importance. Subsequently, up-to-date research works on security solutions for the UAV-aided MEC-enabled IoT are comprehensively presented. To this end, the adoption of information-theoretic techniques that ensure adequate Physical-Layer Security (PLS) is discussed along with sophisticated security approaches based on emerging technologies, such as Blockchain and Machine Learning (ML). In addition, research studies on software-and hardware-based methods for the identification and authentication of network nodes are presented. Finally, this paper provides future perspectives in this research domain, stimulating further work.INDEX TERMS Blockchain, Internet of Things (IoT), Machine Learning (ML), Mobile Edge Computing (MEC), Physical-Layer Security (PLS), Unmanned Aerial Vehicle (UAV).

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“…In particular, the authors in [199] focused on securing the offloaded information against the eavesdropper in an EH and FD relaying protocol employed by UAV-assisted MEC. The expressions of the offloading time, data size, and transmit power were obtained, and additionally, they analyzed the full, partial, and non-offloading conditions.…”

Section: Secured Uav Communications Using Fog Computingmentioning

confidence: 99%

Security Threats and Mitigation Techniques in UAV Communications: A Comprehensive Survey

et al. 2022

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Unmanned aerial vehicles (UAVs) have been instrumental in enabling many new applications and services, including military and rescue operations, aerial surveillance, civilian applications, precision farming, as well as providing extensive wireless network access in remote areas. They have also been used in other areas such as transmission line and oil rig monitoring, disaster recovery, etc. With their increasing payload ability and flight duration, using UAVs is a preferred choice for a multitude of upcoming wireless communication systems. However, because of their open operational nature, UAVs are highly vulnerable to severe security breaches via cyber attacks, eavesdropping on navigational and communication links, etc. Given their widespread applications, the requirement of secured UAV communications has become more and more critical since security failures can lead to detrimental consequences. Several works have examined the extent of privacy and security issues in UAV-assisted networks and introduced various mitigation techniques to address different security challenges. In this paper, a comprehensive survey is conducted that centers on the security issues related to UAV-aided networks. A descriptive taxonomy of various security intrusions on the UAV networks and commonly-used secrecy performance metrics are thoroughly reviewed. An in-depth discussion is provided on alleviating threats with proactive security techniques blended with key wireless communication technologies such as mmWave, non-orthogonal multiple access (NOMA), massive multiple-input multiple-output (MIMO), and cognitive radio. Moreover, several emerging topics like machine learning, software-defined networks, fog and edge computing, blockchain, are discussed in the context of UAV-aided secure communications.INDEX TERMS Physical layer security, unmanned aerial vehicles (UAVs), proactive mitigation techniques, secrecy metrics, emerging wireless technologies.GAURAV KUMAR PANDEY (Graduate Student Member, IEEE) received the B.Tech. degree in electrical and electronics engineering from the

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Secure NOMA-Based UAV-MEC Network Towards a Flying Eavesdropper

Cited by 99 publications

References 39 publications

Design and Optimization of a UAV-Enabled Non-Orthogonal Multiple Access Edge Computing IoT System

Design and Optimization of a UAV-Enabled Non-Orthogonal Multiple Access Edge Computing IoT System

Secure UAV-Aided Mobile Edge Computing for IoT: A Review

Security Threats and Mitigation Techniques in UAV Communications: A Comprehensive Survey

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