Rehman Abdul, Hassan Mohd Fadzil, Yew Kwang Hooi, Paputungan Irving, Tran Duc Chung
Centre for Research and Data Science (CeRDaS), Computer and Information Science Department, Universiti Teknologi Malaysia, Seri Iskandar, Perak Darul Ridzuan, Malaysia.
Informatics Department, Universitas Islam Indonesia, Daerah Istimewa, Yogyakarta, Indonesia.
PeerJ Comput Sci. 2020 Dec 14;6:e334. doi: 10.7717/peerj-cs.334. eCollection 2020.
In the near future, the Internet of Vehicles (IoV) is foreseen to become an inviolable part of smart cities. The integration of vehicular ad hoc networks (VANETs) into the IoV is being driven by the advent of the Internet of Things (IoT) and high-speed communication. However, both the technological and non-technical elements of IoV need to be standardized prior to deployment on the road. This study focuses on trust management (TM) in the IoV/VANETs/ITS (intelligent transport system). Trust has always been important in vehicular networks to ensure safety. A variety of techniques for TM and evaluation have been proposed over the years, yet few comprehensive studies that lay the foundation for the development of a "standard" for TM in IoV have been reported. The motivation behind this study is to examine all the TM models available for vehicular networks to bring together all the techniques from previous studies in this review. The study was carried out using a systematic method in which 31 papers out of 256 research publications were screened. An in-depth analysis of all the TM models was conducted and the strengths and weaknesses of each are highlighted. Considering that solutions based on AI are necessary to meet the requirements of a smart city, our second objective is to analyze the implications of incorporating an AI method based on "context awareness" in a vehicular network. It is evident from mobile ad hoc networks (MANETs) that there is potential for context awareness in ad hoc networks. The findings are expected to contribute significantly to the future formulation of IoVITS standards. In addition, gray areas and open questions for new research dimensions are highlighted.
在不久的将来，车联网有望成为智慧城市不可或缺的一部分。物联网（IoT）的出现和高速通信推动着车载自组网（VANET）融入车联网。然而，在车联网上路部署之前，其技术和非技术要素都需要进行标准化。本研究聚焦于车联网/车载自组网/智能交通系统（ITS）中的信任管理（TM）。在车辆网络中，信任对于确保安全一直都很重要。多年来已经提出了各种信任管理和评估技术，但鲜有全面的研究为车联网中信任管理“标准”的制定奠定基础。本研究的动机是审视所有适用于车辆网络的信任管理模型，以便在本综述中汇总以往研究的所有技术。该研究采用系统方法进行，从256篇研究出版物中筛选出31篇论文。对所有信任管理模型进行了深入分析，并突出了每个模型的优缺点。鉴于基于人工智能的解决方案对于满足智慧城市的需求是必要的，我们的第二个目标是分析在车辆网络中纳入基于“上下文感知”的人工智能方法的影响。从移动自组网（MANET）可以明显看出，自组网中存在上下文感知的潜力。研究结果有望为未来车联网智能交通系统标准的制定做出重大贡献。此外，还突出了新研究维度的灰色地带和开放性问题。
