Survey of Security Protocols and Vulnerabilities in Unmanned Aerial Vehicles

被引:49
作者
Shafique, Arslan [1 ]
Mehmood, Abid [2 ]
Elhadef, Mourad [2 ]
机构
[1] Riphah Int Univ, Dept Elect Engn, Islamabad 46000, Pakistan
[2] Abu Dhabi Univ, Dept Comp Sci & Informat Technol, Abu Dhabi, U Arab Emirates
关键词
Security; Protocols; Drones; Wireless fidelity; Global Positioning System; Privacy; Videos; Unmanned aerial vehicles (UAVs); security; vulnerabilities; attacks; drones; security threats; PHYSICAL LAYER SECURITY; UAV; SURVEILLANCE; NETWORKS; ATTACK; THROUGHPUT; TRACKING; SEARCH; DESIGN; MODEL;
D O I
10.1109/ACCESS.2021.3066778
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the rapid growth in technology, the use of Unmanned Aerial Vehicles (UAVs) have increased in civil and military applications including rescue operations, disaster recovery, and military operations. Despite the utility and advantages of UAVs, they may lead to major security breaches in the context of hardware, software, and communication channel, due their ease of use and availability. UAVs are vulnerable to various types of attacks such as spoofing, false data injection, jamming, fuzzing, availability, confidentiality, and integrity attacks. To overcome these security threats, researchers have been investigating strong security protocols to keep UAVs safe from the attackers. Nevertheless, there are many flaws in the developed protocols which can be exploited by hackers. Therefore, it is becomes crucial to study and analyze the existing security protocols used in UAVs to discover and address their vulnerabilities and weaknesses. The purpose of this study is to explore the vulnerabilities in the security protocols and propose guidelines to improve the security and provide future research directions.
引用
收藏
页码:46927 / 46948
页数:22
相关论文
共 130 条
[1]   Masquerading Attacks Detection in Mobile Ad Hoc Networks [J].
Abbas, Sohail ;
Faisal, Mohammad ;
Rahman, Haseeb Ur ;
Khan, Muhammad Zahid ;
Merabti, Madjid ;
Khan, Atta Ur Rehman .
IEEE ACCESS, 2018, 6 :55013-55025
[2]   Detection of Fault Data Injection Attack on UAV Using Adaptive Neural Network [J].
Abbaspour, Alireza ;
Yen, Kang K. ;
Noei, Shirin ;
Sargolzaei, Arman .
COMPLEX ADAPTIVE SYSTEMS, 2016, 95 :193-200
[3]   A Survey of Security Attacks in Information-Centric Networking [J].
AbdAllah, Eslam G. ;
Hassanein, Hossam S. ;
Zulkernine, Mohammad .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2015, 17 (03) :1441-1454
[4]  
Alala M. J., 2018, INT J COMMUN-US, V3
[5]   Securing Smart City Surveillance: A Lightweight Authentication Mechanism for Unmanned Vehicles [J].
Ali, Zeeshan ;
Chaudhry, Shehzad Ashraf ;
Ramzan, Muhammad Sher ;
Al-Turjman, Fadi .
IEEE ACCESS, 2020, 8 :43711-43724
[6]   PARTH: A two-stage lightweight mutual authentication protocol for UAV surveillance networks [J].
Alladi, Tejasvi ;
Chamola, Vinay ;
Naren ;
Kumar, Neeraj .
COMPUTER COMMUNICATIONS, 2020, 160 (160) :81-90
[7]  
Amelin Konstantin, 2015, IFAC - Papers Online, V48, P233, DOI 10.1016/j.ifacol.2015.09.189
[8]  
[Anonymous], 2020, IEEE ACCESS
[9]  
[Anonymous], 2016, 10 USENIX WORKSHOP O
[10]   Machine Learning Inspired Sound-Based Amateur Drone Detection for Public Safety Applications [J].
Anwar, Muhammad Zohaib ;
Kaleem, Zeeshan ;
Jamalipour, Abbas .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (03) :2526-2534