Secure Throughput Optimization for Cache-Enabled Multi-UAVs Networks

Fazel, Fahimeh; Abouei, Jamshid; Jaseemuddin, Muhammad; Anpalagan, Alagan; Plataniotis, Konstantinos N.

doi:10.1109/jiot.2021.3114086

Cited by 22 publications

(7 citation statements)

References 40 publications

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“…A dynamic power allocation and an aerial jamming technique for UAV-assisted NOMA communication networks have been studied by the authors in [178] to enhance the reliability and security in the presence of a terrestrial eavesdropper. Whereas the authors in [179] have considered an ultra-dense heterogeneous network of cache-aided UAVs employing power domain NOMA protocol and IoT-mobile devices. They have aimed to maximize the secured cache throughput by optimizing the UAV's 3-D positions, number of UAVs and mobile devices, and UAV's cache placement probability by employing fast global K-means and iterative algorithms.…”

Section: Uav-aided Noma and Beamforming Methodsmentioning

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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Section: Uav-aided Noma and Beamforming Methodsmentioning

confidence: 99%

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

et al. 2022

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“…While the authors in [18]- [22] propose content placement strategies to maximize content availability, improve successful content delivery and reduce energy consumption, they fail to consider UAV deployment strategy. As a matter of fact, it can be demonstrated that caching efficiency can be enhanced by jointly designing UAV deployment and content caching strategies [23]- [28]. The research works in [23], [24] propose content placement schemes and UAV deployment strategies to maximize throughput [23] or coverage probability [24].…”

Section: A Literature Reviewmentioning

confidence: 99%

“…The researchers in [25], [26] define the quality of experience (QoE) and present joint UAV deployment and caching placement strategies to maximize mean opinion score [25] or maximize the average content delay index [26]. In [27], [28], the authors design joint UAV deployment and content placement algorithms to minimize the sum cost of energy consumption and file delivery delay [27] or maximize secure throughput [28].…”

Section: A Literature Reviewmentioning

confidence: 99%

“…Hence, designing proactive caching strategy with unknown user requests becomes particularly important. On the other hand, current research mainly performs joint UAV deployment and caching based on user location information and rarely considers the impact of user request distribution on UAV deployment [23]- [28]. Indeed, it can be demonstrated that designing UAV deployment and caching strategy which takes into account user content request is expected to improve content delivery performance and caching efficiency as well.…”

Section: B Motivation and Contributionsmentioning

confidence: 99%

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Content Fetching Delay Optimization-Based Caching and Resource Allocation for UAV-Enabled Networks

Bayessa,

Chai,

Liang

et al. 2024

IEEE Access

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In this work, we investigate content caching problem in unmanned aerial vehicle (UAV)enabled networks where UAVs are allowed to store user requested content so as to enhance the content transmission performance of users. To predict user content request, we propose a bidirectional long shortterm memory-based algorithm. Then, the content transmission delay of users is examined and the UAV deployment, content caching and resource allocation problem is formulated as an overall content fetching delay minimization problem. As the formulated problem is difficult to solve, we transform it into two subproblems which are solved iteratively. To tackle the UAV deployment and content caching subproblem, we first design a modified K-means-based clustering scheme and then propose a UAV deployment strategy by using quadratic transformation. To solve subcarrier and power allocation subproblem, we apply Lagrangian dual method to determine power allocation strategy and propose a Kuhn-Munkres algorithm-based subcarrier allocation strategy. Simulation results show that our approach achieves approximately 11.1% lower overall content fetching delay compared to the existing algorithm.INDEX TERMS Unmanned aerial vehicles, user clustering, UAV deployment, content caching, resource allocation.

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“…The altitude of the UAV [32], H 100 m The reference channel power gain [32], β 0 −60 dB The level of the UAV's self-inference [15], ω −120 dB The noise power [26] , σ 2 −110 dB The maximum speed of the UAV [32], V max 50 m/s The length of each time slot [26], θ 0.5 s The minimum tolerable data received [23], ξ, 100 Kbit The power of the UAV and ground nodes [33], P u , P m , 10 dBm The maximum SOP\COP constraint [34], φ sout \φ cout , 0.05…”

Section: Parameters Valuesmentioning

confidence: 99%

Energy Consumption Minimization in Unmanned Aerial Vehicle-Enabled Secure Wireless Sensor Networks

Ding,

Tian,

Liu

et al. 2023

Sensors

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In wireless sensor networks (WSNs), unmanned aerial vehicles (UAVs) are considered an effective data collection tool. In this paper, we investigate the energy-efficient data collection problem in a UAV-enabled secure WSN without knowing the instantaneous channel state information of the eavesdropper (Eve). Specifically, the UAV collected the information from all the wireless sensors at the scheduled time and forward it to the fusion center while Eve tries to eavesdrop on this confidential information from the UAV. To surmount this intractable and convoluted mixed-integer non-convex problem, we propose an efficient iterative optimization algorithm using the block coordinate descent (BCD) method to minimize the maximum energy consumption of the ground sensor nodes (GSNs) under the constraints of secrecy outage probability (SOP), connection outage probability (COP), minimum secure data, information causality, and UAV trajectory. Numerical results demonstrate the superiority of the algorithm we proposed in energy consumption and secrecy rate compared with other schemes.

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Secure Throughput Optimization for Cache-Enabled Multi-UAVs Networks

Cited by 22 publications

References 40 publications

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

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

Content Fetching Delay Optimization-Based Caching and Resource Allocation for UAV-Enabled Networks

Energy Consumption Minimization in Unmanned Aerial Vehicle-Enabled Secure Wireless Sensor Networks

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