An overview of VANET vehicular networks

Today, with the development of intercity and metropolitan roadways and with various cars moving in various directions, there is a greater need than ever for a network to coordinate commutes. Nowadays, people spend a lot of time in their vehicles. Smart automobiles have developed to make that time safer, more effective, more fun, pollution-free, and affordable. However, maintaining the optimum use of resources and addressing rising needs continues to be a challenge given the popularity of vehicle users and the growing diversity of requests for various services. As a result, VANET will require modernized working practices in the future. Modern intelligent transportation management and driver assistance systems are created using cutting-edge communication technology. Vehicular Ad-hoc networks promise to increase transportation effectiveness, accident prevention, and pedestrian comfort by allowing automobiles and road infrastructure to communicate entertainment and traffic information. By constructing thorough frameworks, workflow patterns, and update procedures, including block-chain, artificial intelligence, and SDN (Software Defined Networking), this paper addresses VANET-related technologies, future advances, and related challenges. An overview of the VANET upgrade solution is given in this document in order to handle potential future problems

Hardware accelerated authentication system for dynamic time-critical networks

The secure and efficient operation of time-critical networks, such as vehicular networks, smart-grid and other smart-infrastructures, is of primary importance in today’s society. It is crucial to minimize the impact of security mechanisms over such networks so that the safe and reliable operations of time-critical systems are not being interfered. Even though there are several security mechanisms, their application to smart-infrastructure and Internet of Things (IoT) deployments may not meet the ubiquitous and time-sensitive needs of these systems. That is, existing security mechanisms either introduce a significant computation and communication overhead, or they are not scalable for a large number of IoT components. In particular, as a primary authentication mechanism, existing digital signatures cannot meet the real-time processing requirements of time-critical networks, and also do not fully benefit from advancements in the underlying hardware/software of IoTs. As a part of this thesis, we create a reliable and scalable authentication system to ensure secure and reliable operation of dynamic time-critical networks like vehicular networks through hardware acceleration. The system is implemented on System-On-Chips (SoC) leveraging the parallel processing capabilities of the embedded Graphical Processing Units (GPUs) along with the CPUs (Central Processing Units). We identify a set of cryptographic authentication mechanisms, which consist of operations that are highly parallelizable while still maintain high standards of security and are also secure against various malicious adversaries. We also focus on creating a fully functional prototype of the system which we call a “Dynamic Scheduler” which will take care of scheduling the messages for signing or verification on the basis of their priority level and the number of messages currently in the system, so as to derive maximum throughput or minimum latency from the system, whatever the requirement may be

Towards Cyber Security for Low-Carbon Transportation: Overview, Challenges and Future Directions

In recent years, low-carbon transportation has become an indispensable part as sustainable development strategies of various countries, and plays a very important responsibility in promoting low-carbon cities. However, the security of low-carbon transportation has been threatened from various ways. For example, denial of service attacks pose a great threat to the electric vehicles and vehicle-to-grid networks. To minimize these threats, several methods have been proposed to defense against them. Yet, these methods are only for certain types of scenarios or attacks. Therefore, this review addresses security aspect from holistic view, provides the overview, challenges and future directions of cyber security technologies in low-carbon transportation. Firstly, based on the concept and importance of low-carbon transportation, this review positions the low-carbon transportation services. Then, with the perspective of network architecture and communication mode, this review classifies its typical attack risks. The corresponding defense technologies and relevant security suggestions are further reviewed from perspective of data security, network management security and network application security. Finally, in view of the long term development of low-carbon transportation, future research directions have been concerned.Comment: 34 pages, 6 figures, accepted by journal Renewable and Sustainable Energy Review

Machine Learning for Unmanned Aerial System (UAS) Networking

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale. With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring. This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS

Information management and security protection for internet of vehicles

Considering the huge number of vehicles on the roads, the Internet of Vehicles is envisioned to foster a variety of new applications ranging from road safety enhancement to mobile entertainment. These new applications all face critical challenges which are how to handle a large volume of data streams of various kinds and how the secure architecture enhances the security of the Internet of Vehicles systems. This dissertation proposes a comprehensive message routing solution to provide the fundamental support of information management for the Internet of Vehicles. The proposed approach delivers messages via a self-organized moving-zone-based architecture formed using pure vehicle-to-vehicle communication and integrates moving object modeling and indexing techniques to vehicle management. It can significantly reduce the communication overhead while providing higher delivery rates. To ensure the identity and location privacy of the vehicles on the Internet of Vehicles environment, a highly efficient randomized authentication protocol, RAU+ is proposed to leverage homomorphic encryption and enable individual vehicles to easily generate a new randomized identity for each newly established communication while each authentication server would not know their real identities. In this way, not any single party can track the user. To minimize the infrastructure reliance, this dissertation further proposes a secure and lightweight identity management mechanism in which vehicles only need to contact a central authority once to obtain a global identity. Vehicles take turns serving as the captain authentication unit in self-organized groups. The local identities are computed from the vehicle's global identity and do not reveal true identities. Extensive experiments are conducted under a variety of Internet of Vehicles environments. The experimental results demonstrate the practicality, effectiveness, and efficiency of the proposed protocols.Includes bibliographical references