Department of Computer Science and Information, Taibah University, Medina 42353, Saudi Arabia.
Department of Computer Science and Electronics, Ramakrishna Mission Vidyamandira, Belur Math, Howrah 711202, West Bengal, India.
Sensors (Basel). 2022 Feb 20;22(4):1652. doi: 10.3390/s22041652.
Information fusion in automated vehicle for various datatypes emanating from many resources is the foundation for making choices in intelligent transportation autonomous cars. To facilitate data sharing, a variety of communication methods have been integrated to build a diverse V2X infrastructure. However, information fusion security frameworks are currently intended for specific application instances, that are insufficient to fulfill the overall requirements of Mutual Intelligent Transportation Systems (MITS). In this work, a data fusion security infrastructure has been developed with varying degrees of trust. Furthermore, in the V2X heterogeneous networks, this paper offers an efficient and effective information fusion security mechanism for multiple sources and multiple type data sharing. An area-based PKI architecture with speed provided by a Graphic Processing Unit (GPU) is given in especially for artificial neural synchronization-based quick group key exchange. A parametric test is performed to ensure that the proposed data fusion trust solution meets the stringent delay requirements of V2X systems. The efficiency of the suggested method is tested, and the results show that it surpasses similar strategies already in use.
信息融合在自动化车辆中对于各种源自多种资源的数据类型是智能交通自主汽车做出决策的基础。为了促进数据共享，已经集成了各种通信方法来构建多样化的 V2X 基础设施。然而，信息融合安全框架目前针对特定的应用实例，不足以满足互智能交通系统（MITS）的总体要求。在这项工作中，已经开发了具有不同信任度的数据融合安全基础设施。此外，在 V2X 异构网络中，本文为多源和多类型数据共享提供了一种高效、有效的信息融合安全机制。特别是对于基于图形处理单元（GPU）提供速度的基于区域的 PKI 架构，提出了一种基于人工神经网络同步的快速群组密钥交换方法。进行了参数测试，以确保所提出的数据融合信任解决方案满足 V2X 系统严格的延迟要求。测试了所提出方法的效率，结果表明它超过了现有的类似策略。
