4.7 Review

A comprehensive survey on security, privacy issues and emerging defence technologies for UAVs

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ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jnca.2023.103607

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Cyber security and privacy; Vulnerabilities; Adversarial machine learning; Intrusion detection system; Digital forensic; Blockchain

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The rapid development of the UAV industry in the past two decades has led to an increase in the use of commercial UAVs. However, the lack of security measures has introduced numerous threats and vulnerabilities. This research review provides a comprehensive survey of privacy and security issues in UAVs, presents existing mitigation techniques, and discusses emerging technologies for protecting UAVs, such as blockchain, machine learning, intrusion detection systems, and secure communication protocols.
In the past two decades, there has been a rapid development in the drone industry known as Unmanned Aerial Vehicles (UAVs). Currently, the use of commercial UAVs has increased a lot due to their affordability, but lack of security implementations has introduced many threats and vulnerabilities in UAVs. In addition, software, and hardware complexity in UAVs also triggers privacy and security issues as well as causes critical challenges for government, industry and academia. Firstly, in this research review, we broadly survey privacy and security issues of UAVs by dividing them into three classes: Software, Hardware and Communication. Particularly, for each class, we systematically survey the common vulnerabilities causing potential attacks to UAVs. Secondly, a review of prevailing threats that are threatening civilian UAVs' applications is also a part of this survey. Thirdly, a comprehensive discussion of passive and active attacks from adversaries, for compromising privacy and security of UAVs is given as well. Fourthly, we provide detail description of existing mitigation techniques and countermeasures, to protect UAVs. Fifthly, the solution architecture part includes discussion about emerging technologies such as, blockchain usage, machine learning, intrusion detection systems and secure communication protocols. To store all data in transit, blockchain can be used cryptographically and protect it from eavesdropping and tampering. In this research review, key points that highlighted the lessons learned about security and privacy of UAVs are also summarized. Lastly, the survey is concluded by discussing important pitfalls as well as suggestions for future research directions, concerning privacy and security of UAVs.

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