Drone Transportation System: Systematic Review of Security Dynamics for Smart Mobility

被引:19
作者
Ajakwe, Simeon Okechukwu [1 ]
Kim, Dong-Seong [1 ]
Lee, Jae-Min [1 ]
机构
[1] Kumoh Natl Inst Technol, Dept IT Convergence Engn, Gumi 39177, South Korea
关键词
Artificial intelligence (AI); blockchain; digital twin (DT); drone transportation system (DTS); metaverse; non-fungible token (NFT); security; unmanned aerial vehicle (UAV); CHALLENGES; INTERNET; SCHEME; IOT; TECHNOLOGIES; ARCHITECTURE; TRACKING; FUTURE;
D O I
10.1109/JIOT.2023.3266843
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The intelligence and integrity of a real-time cyber-physical system depend on how trustworthy the data's legitimacy, appropriation, and authorization are during end-to-end communication between the participating nodes in its network. With the recurrent repugnant global violations of the airspace by drones and their derivatives, there is an urgent need to empirically evaluate the underlying security architectures that govern drone usage operations for priority logistics. This review examines the significant contribution of artificial intelligence models and blockchain to the development of trustworthy and reliable intelligent and secure autonomous systems by integrating cyberspace, intelligence space, and airspace security. PRISMA-SPIDER methodology was adopted for the systematic review of 133 articles based on the inclusion criteria consisting of 91 (68.4%) quantitative studies, 19 qualitative studies (14.2%), and 23 (17.3%) mixed method studies to balance article selection sensitivity and specificity. The review outcome shows a significant disconnect between model proposals and actual implementation. Through the incorporation of zero-trust architecture into the existing blockchain technology and the convergence of newer AI models, dynamic security issues like drone ownership authentication, drone package delivery verification, drone operation authorization, and drone jurisdiction accountability, can be achieved seamlessly for secure smart mobility via drone transportation systems.
引用
收藏
页码:14462 / 14482
页数:21
相关论文
共 150 条
  • [31] [Anonymous], 2023, UAS sightings report
  • [32] [Anonymous], 2009, Business Standard
  • [33] [Anonymous], 2019, FACT SHEET FED AV AD
  • [34] [Anonymous], 2018, TELEGRAPH DEC
  • [35] [Anonymous], 2018, Bloomberg
  • [36] [Anonymous], 2020, WORLD TIMES
  • [37] Combined RF-Based Drone Detection and Classification
    Basak, Sanjoy
    Rajendran, Sreeraj
    Pollin, Sofie
    Scheers, Bart
    [J]. IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2022, 8 (01) : 111 - 120
  • [38] Basu Deborsi, 2022, DroneCom '22: Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond, P13, DOI 10.1145/3555661.3560857
  • [39] Unmanned Aerial Vehicles' Remote Identification: A Tutorial and Survey
    Belwafi, Kais
    Alkadi, Ruba
    Alameri, Sultan A.
    Al Hamadi, Hussam
    Shoufan, Abdulhadi
    [J]. IEEE ACCESS, 2022, 10 : 87577 - 87601
  • [40] Blockchain-Envisioned Secure Data Delivery and Collection Scheme for 5G-Based IoT-Enabled Internet of Drones Environment
    Bera, Basudeb
    Saha, Sourav
    Das, Ashok Kumar
    Kumar, Neeraj
    Lorenz, Pascal
    Alazab, Mamoun
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (08) : 9097 - 9111