Security and Privacy for the Internet of Drones: Challenges and Solutions

Lin, Chao; He, Debiao; Kumar, Neeraj; Choo, Kim‐Kwang Raymond; Vinel, Alexey; Huang, Xinyi

doi:10.1109/mcom.2017.1700390

Cited by 296 publications

(149 citation statements)

References 15 publications

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“…Thus, the privacy leakage needs to be considered in the design of a security solution for the UAV networks. In [287], the authors study the security and privacy requirements of the internet of UAVs, and outline potential solutions to address challenging issues, including the privacy leakage, data confidentiality protection and flexible accessibility. In [286], the authors have surveyed the main security, privacy and safety aspects associated with the civilian drone usage in the national airspace.…”

Section: F Security and Privacymentioning

confidence: 99%

Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System Perspective

Wang

Zhao

Zhang

et al. 2020

IEEE Commun. Surv. Tutorials

173

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Unmanned aerial vehicle (UAV) networks are playing an important role in various areas due to their agility and versatility, which have attracted significant attention from both the academia and industry in recent years. As an integration of the embedded systems with communication devices, computation capabilities and control modules, the UAV network could build a closed loop from data perceiving, information exchanging, decision making to the final execution, which tightly integrates the cyber processes into the physical devices. Therefore, the UAV network could be considered as a cyber physical system (CPS). Revealing the coupling effects among the three interacted components in this CPS system, i.e., communication, computation and control, is envisioned as the key to properly utilize all the available resources and hence improve the performance of the UAV networks. In this paper, we present a comprehensive survey on the UAV networks from a CPS perspective. Firstly, we respectively research the basics and advances with respect to the three CPS components in the UAV networks. Then we look inside to investigate how these components contribute to the system performance by classifying the UAV networks into three hierarchies, i.e., the cell level, the system level, and the system of system level. Further, the coupling effects among these CPS components are explicitly illustrated, which could be enlightening to deal with the challenges in each individual aspect. New research directions and open issues are discussed at the end of this survey. With this intensive literature review, we try to provide a novel insight into the state-of-the-art in the UAV networks.

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Section: F Security and Privacymentioning

confidence: 99%

Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System Perspective

Wang

Zhao

Zhang

et al. 2020

IEEE Commun. Surv. Tutorials

173

View full text Add to dashboard Cite

show abstract

“…Safety requirements, among many functional and nonfunctional requirements, are critical for transportation systems such as drones [46]. Although several attempts exist for safety assurance, incidents of drones still happen, often leading to interference in other transport systems like passenger aircraft and airports.…”

Section: Related Workmentioning

confidence: 99%

Cautious Adaptation of Defiant Components

Maia

Vieira

Chagas

et al. 2019

2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)

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Systems-of-systems are formed by the composition of independently created software components. These components are designed to satisfy their individual requirements, rather than the global requirements of the systems-of-systems. We refer to components that cannot be adapted to meet both individual and global requirements as "defiant" components. In this paper, we propose a "cautious" adaptation approach which supports changing the behaviour of such defiant components under exceptional conditions to satisfy global requirements, while continuing to guarantee the satisfaction of the components' individual requirements. The approach represents both normal and exceptional conditions as scenarios; models the behaviour of exceptional conditions as wrappers implemented using an aspect-oriented technique; and deals with both single and multiple instances of defiant components with different precedence order at runtime. We evaluated an implementation of the approach using drones and boats for an organ delivery application conceived by our industrial partners, in which we assess how the proposed approach helps achieve the systemof-systems' global requirements while accommodating increased complexity of hybrid aspects such as multiplicity, precedence ordering, openness, and heterogeneity.

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“…They contain air-to-ground channel modeling [4], resource and trajectory optimization [5], and spectrum management [6]. Moreover, cellular networks need to be planned [7] as a new MAC layer design is required [8] and security issues need to be addressed [9]. In this paper, trajectory and resources are optimized jointly based on the users' location.…”

Section: Introductionmentioning

confidence: 99%

Base-Stations Up in the Air: Multi-UAV Trajectory Control for Min-Rate Maximization in Uplink C-RAN

Roth

Kariminezhad

Sezgin

2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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In this paper we study the impact of unmanned aerial vehicles (UAVs) trajectories on terrestrial users' spectral efficiency (SE). Assuming a strong line of sight path to the users, the distance from all users to all UAVs influence the outcome of an online trajectory optimization. The trajectory should be designed in a way that the fairness rate is maximized over time. That means, the UAVs travel in the directions that maximize the minimum of the users' SE. From the free-space path-loss channel model, a data-rate gradient is calculated and used to direct the UAVs in a long-term perspective towards the local optimal solution on the two-dimensional spatial grid. Therefore, a control system implementation is designed. Thereby, the UAVs follow the data-rate gradient direction while having a more smooth trajectory compared with a gradient method. The system can react to changes of the user locations online; this system design captures the interaction between multiple UAV trajectories by joint processing at the central unit, e.g., a ground base station. Because of the wide spread of user locations, the UAVs end up in optimal locations widely apart from each other. Besides, the SE expectancy is enhancing continuously while moving along this trajectory.

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Security and Privacy for the Internet of Drones: Challenges and Solutions

Cited by 296 publications

References 15 publications

Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System Perspective

Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System Perspective

Cautious Adaptation of Defiant Components

Base-Stations Up in the Air: Multi-UAV Trajectory Control for Min-Rate Maximization in Uplink C-RAN

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