Construction of Efficient Authenticated Key Agreement Protocol for Intelligent Transportation System

An intelligent transportation System (ITS) is an unconventional application that aims to provide traffic congestion information and emergency information to other vehicles. In ITS, the compilation and distribution of traffic event information by vehicles are of the most extreme significance. To establish an effective data-sharing network in ITS, the vehicles need to share the data in a protected form in real-time. Conventional ITS system includes data streaming from On-Board Unit (OBU) sensors through Road Side Units (RSU) to centralized cloud servers. Nevertheless, it is still a challenge to distribute essential event information in a selected area under the dynamic ITS environment and in the existence of a malicious vehicle. The current fundamental issues which emerge include privacy concerns due to third party management of cloud servers, single point of failure which are a bottleneck in data flow among the vehicles.

Recent advances in wireless communication, sensing, computation and control technologies have paved the way for the development of a new era of Internet of Vehicles (IoV). Demanded by the requirements of information-centric and data-driven intelligent transportation systems (ITS), it is of great significance to explore new paradigms of IoV in supporting large-scale, real-time, and reliable information services. In this article, we propose a hierarchical system architecture, which aims at synthesizing the paradigms of software defined networking and fog computing in IoV and best exploiting their synergistic effects on information services. Specifically, a four-layer architecture is designed, comprising the application layer, the control layer, the virtualization layer, and the data layer, with objectives of enabling logically centralized control via the separation of the control plane and the data plane; facilitating adaptive resource allocation and QoS oriented services based on network functions virtualization and network slicing, and enhancing system scalability, responsiveness, and reliability by exploiting the networking, computation, communication, and storage capacities of fog-based services. On this basis, we further analyze newly arising challenges and discuss future research directions by presenting a cross-layer protocol stack. Finally, for the proof of concept, we implement the system prototype and give two case studies in real-world IoV environments. The results of field tests not only demonstrate the great potential of the new architecture, but also give insight into the development of future ITS.

The Internet of Vehicles (IoV) is becoming an interesting topic among researchers and it has emerged as a rapidly advancing field within Vehicular Ad-hoc Networks, facilitating intelligent communication between vehicles and the cloud through the integration of Internet of Things (IoT) technologies. The IoV surroundings face serious challenges due to the highly interrelated nature of vehicles and infrastructure in certifying privacy and security. Traditional approaches to authentication lack the strength required to protect against developing fears, leaving systems vulnerable to attacks. This survey addresses the gap by employing formal analysis approaches to prove authentication protocols, targeting to reinforce safety and confidentiality in IoV systems. The IoV communication model consists of Vehicle-to-Vehicle, Vehicle-to-Infrastructure, Vehicle-to-Personal Devices, and Vehicle-to-Cloud. Smart automobiles are equipped with cameras, radars, on-board units, and sensors to help reduce the number of accidents by giving drivers or autonomous vehicles up-to-date information on roads, traffic signals, and other pertinent entities. As human lives are at risk, security and privacy in the IoV communication paradigm are critical and cannot neglected. Security and privacy breaches may cause accidents because the attacker can inject false information into the system as the communication channel is open and unsecured. The researchers proposed many authentication protocols to provide secure communication between IoV entities. Although surveys on IoV security and privacy issues deal with communication and computation costs, they lack formal analysis of the authentication protocols. This survey reviews the informal analysis and formal analysis methods used by various authentication protocols. Furthermore, the challenges and future work are also included in this survey.

In the Internet of Vehicles (IoV), numerous potential applications have come up with the use of the Internet of Things (IoT)-empowered smart devices. In IoV, vehicles, roads, street signs and traffic lights can accordingly adjust to changing conditions in order to assist drivers, and also to improve safety, ease congestion and pollution reduction. Since various entities in an IoV environment make communications over public channels, there are potential security threats. To deal with such serious threats, we design a new blockchain-assisted certificateless key agreement protocol for IoV in smart transportation context, called Block-CLAP. In Block-CLAP, through authentication key management, traffic-centric data reach to a cluster head (CH) and then to its nearby road-side unit (RSU) securely using the established secret keys. A cloud server (CS) then securely collects the information from its attached RSUs and create the transactions. Later, the transactions are formed into blocks by the CS in a Peer-to-Peer (P2P) cloud servers network, and the blocks are verified and added through voting-based consensus algorithm in the blockchain. The detailed security analysis through formal, informal and formal security verification, and comparative study show that Block-CLAP provides superior security and has low communication and computational overheads as compared with other existing competing authentication schemes in the IoV environment. Finally, the blockchain-based implementation of Block-CLAP has been performed to measure computational time needed for a varied number of transactions per block and also for a varied number of blocks mined in the blockchain.

Intelligent Transportation System (ITS) and Internet of Vehicles (IoV) allows the vehicles to disseminate and exchange various messages among nearby vehicles in the network. It includes road safety, road accidents, location sharing, driver assistance, navigation, collision warning, traffic data, and toll payment. Moreover, the exchange of these messages is carried out in an insecure channel. Hence, it leads to several issues during transmission of these messages in resource constrained IoV networks. It includes reliable data dissemination, dynamic topology, mobility of the vehicles, vehicle user’s privacy, and lightweight authentication mechanism. The existing Vehicle to Vehicle (V2V) data dissemination techniques have limitations in security attacks such as side channel, device stolen, cloning attacks, high computational overhead, throughput, and high communication cost. In this article, we propose P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> IoV: Privacy Preserving Lightweight Secure (V2V) Data Dissemination Scheme for IoV environment using lightweight cryptographic primitives such as SHA-256, concatenation and XoR operation. We evaluate P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> IoV in terms of security and vehicle user’s privacy against several security attacks. We do an in-depth security analysis of the P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> IoV by using informal security analysis and provides security proofs. We also perform a comparative analysis of P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> IoV with the existing state-of-the-art IoV environment using various performance parameters. The test-bed experimental result shows that P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> IoV outperforms the existing V2V data dissemination technique in terms of computational cost, communication overhead, and energy consumption.

Internet of Vehicles (IoV) is an emerging concept that is believed to help realize the vision of intelligent transportation systems (ITSs). IoV has become an important research area of impactful applications in recent years due to the rapid advancements in vehicular technologies, high throughput satellite communication, the Internet of Things, and cyber-physical systems. IoV enables the integration of smart vehicles with the Internet and system components attributing to their environments, such as public infrastructures, sensors, computing nodes, pedestrians, and other vehicles. By allowing the development of a common information exchange platform between vehicles and heterogeneous vehicular networks, this integration aims to create a better environment and public space for the people as well as to enhance safety for all road users. Being a participatory data exchange and storage, the underlying information exchange platform of IoV needs to be secure, transparent, and immutable in order to achieve the intended objectives of ITS. In this connection, the adoption of blockchain as a system platform for supporting the information exchange needs of IoV has been explored. Due to their decentralized and immutable nature, IoV applications enabled by blockchain are believed to have a number of desirable properties, such as decentralization, security, transparency, immutability, and automation. In this article, we present a contemporary survey on the latest advancement in blockchain for IoV. Particularly, we highlight the different application scenarios of IoV after carefully reviewing the recent literature. We also investigate several key challenges where blockchain is applied in IoV. Furthermore, we present the future opportunities and explore further research directions of IoV as a key enabler of ITS.

The Internet of Vehicles (IoV) is expected to become the central infrastructure to provide advanced services to connected vehicles and users for higher transportation efficiency and security. A variety of emerging applications/services bring explosively growing demands for mobile data traffic between connected vehicles and roadside units (RSUs), imposing the significant challenge of spectrum scarcity in the IoV. In this article, we propose a cooperative semantic-aware architecture to convey essential semantics from collaborated users to servers for lessening data traffic. In contrast to current solutions that are mainly based on piling up highly complex signal processing techniques and multiple access capabilities in terms of syntactic communications, this article puts forth the idea of semantic-aware content delivery in the IoV. Specifically, the successful transmission of essential semantics of the source data is pursued rather than the accurate reception of symbols regardless of their meaning, as in conventional syntactic communications. To assess the benefits of the proposed architecture, we provide a case study of an image retrieval task for vehicles in intelligent transportation systems (ITSs). Simulation results demonstrate that the proposed architecture outperforms existing solutions, with fewer radio resources, especially in a low-signal-to-noise-ratio (SNR) regime, which can shed light on the potential of the proposed architecture in extending applications in extreme environments.

One of the most important components of intelligent transportation systems (ITS) is the automotive self-organizing VANET network (vehicular ad hoc network). Its nodes are vehicles with specialized onboard units (OBU) installed on them. Such a network can be subject to various attacks. To reduce the effectiveness of a number of attacks on the VANET, it is advisable to use authentication protocols. Well-known authentication protocols support a security policy with full trust in roadside unit (RSU) base stations. The disadvantage of these authentication protocols is the ability of the RSU to track the route of the vehicle. This leads to a violation of the privacy and anonymity of the vehicle’s owner. To eliminate this drawback, the article proposes an adaptive authentication protocol. An advantage of this protocol is the provision of high imitation resistance without using symmetric and asymmetric ciphers. This result has been achieved by using a zero-knowledge authentication protocol. A scheme for adapting the protocol parameters depending on the intensity of the user’s traffic has been developed for the proposed protocol. The scientific novelty of this solution is to reduce time spent on authentication without changing the protocol execution algorithm by reducing the number of modular exponentiation operations when calculating true and “distorted” digests of the prover and verifying the correctness of responses, as well as by reducing the number of responses. Authentication, as before, takes place in one round without changing the bit depth of the modulus used in the protocol. To evaluate the effectiveness of the adaptive authentication protocol, the VANET model was implemented using NS-2. The obtained research results have shown that the adaptation of the authentication protocol in conditions of increased density of vehicles on the road makes it possible to increase the volume of data exchange between OBU and RSU by reducing the level of confidentiality. In addition, a mechanism for verifying the authority of the vehicle’s owner for provided services has been developed. As a result of the implementation of this mechanism, vehicle registration sites (VRS) calculate the public key of the vehicle without using encryption and provide necessary services to the owner.

The convergence of vehicular technology, artificial intelligence (AI), and distributed computing has catalyzed the emergence of the Internet of Vehicles (IoV) as a cornerstone of next-generation intelligent transportation systems (ITS). By enabling vehicle-to-everything (V2X) communication, IoV supports cooperative perception, real-time decision-making, and autonomous driving. However, the reliance on large-scale, data-driven intelligence in IoV exposes systems to critical challenges, including adversarial poisoning, privacy leakage, identity forgery, and the fragility of centralized learning architectures. Federated Learning (FL) has been proposed as a promising paradigm to alleviate some of these issues by enabling distributed model training without centralizing sensitive vehicular data. Nonetheless, conventional FL remains vulnerable to security and trust limitations, particularly in dynamic vehicular environments. This thesis addresses these challenges by designing secure, privacy-preserving, and scalable FL frameworks that leverage distributed ledger technologies and cutting-edge security mechanisms.The thesis advances knowledge through four interconnected contributions. First, two novel optimization-driven poisoning attack models are introduced: PA-PSOSA and PAPSOGA, which combine particle swarm optimization with simulated annealing and genetic algorithms, respectively. These models demonstrate that even a small poisoning budget can substantially degrade global model utility under black-box and clean-label constraints, highlighting the urgency of robust defenses in vehicular FL. Second, a permissioned blockchain-enabled FL (BCFL) framework is proposed, in which consortium edge nodes running Practical Byzantine Fault Tolerance (PBFT) consensus replace the central aggregator. With blockchain integration and data validation mechanisms, this design ensures identity authentication, verifiable audit trails, and improved resilience against poisoning and Sybil attacks, while maintaining high model accuracy under adversarial conditions. Third, the framework is further enhanced to achieve inference-resistance by integrating secure aggregation (SecAgg) and differential privacy (DP), and lightweight with off-chain commitments. This design significantly reduces ledger storage requirements, increases system throughput, and mitigates inference-based privacy risks. Finally, to overcome the scalability limitations of PBFT-based BCFL, a DAG-enabled FL (DFL) framework is developed. By leveraging parallel validation, utility-score-based tip selection, and reputation-weighted aggregation, this framework significantly improves scalability, reduces communication complexity, and enhances robustness in asynchronous vehicular environments.Together, these contributions articulate a coherent progression from exposing vulnerabilities in vehicular FL to constructing secure, privacy-preserving, and scalable frameworks tailored for IoV ecosystems. The findings demonstrate that interdisciplinary integration of optimization theory, cryptography, differential privacy, and distributed ledger technologies is indispensable for trustworthy vehicular intelligence. Beyond theoretical significance, the proposed frameworks offer practical designs for deployment in safety-critical IoV environments. Future research directions include the integration of zero-knowledge proofs (ZKP) for verifiable privacy, adaptive defenses against evolving adversarial strategies, and experimental validation in real-world vehicular testbeds. Collectively, this thesis establishes a foundation for secure federated intelligence in IoV, contributing to the reliability, efficiency, and trustworthiness of next-generation ITS.

Radio‐frequency identification (RFID) technology has proliferated over the last few years and being deployed as identification technology in numerous domains like intelligent transportation systems (ITS) and Internet of Vehicles (IoV) for applications like road safety, efficient traffic management, automatic toll collection, intelligent parking, etc. As RFID devices, as well as the possible domains of ITS and IoV onto which the RFID technology can be deployed, are usually resource‐constrained, thus, security and privacy become a major concern. So, public‐key cryptography becomes the better choice for enhancing the security of RFID based systems. Elliptic curve cryptography (ECC) is one of the dominant and secure asymmetric‐key cryptosystems being used for RFID security due to its smaller key size. Numerous RFID authentication schemes based on ECC have been suggested in literature, however, the majority has various serious security weaknesses. To bridge those existing security weaknesses, an enhanced ECC based light weight protocol for RFID systems has been proposed in this article. An extensive security analysis has been performed to demonstrate various secure features offered by our proposed protocol, and formal security analysis is being conducted using Automated Validation of Internet Security Protocols and Applications tool. The performance of our proposed RFID protocol has been compared with various existing RFID based security solutions on the basis of parameters, that is, computational cost, communication cost, and storage requirement. Simulation results indicate that the proposed lightweight protocol is more secure and performance efficient than the existing RFID protocols, and is well suited for practical applications.

The mobility status of self and surrounding vehicles provides important information to various tasks in autonomous driving (AD) and intelligent transportation system (ITS). Accordingly, a precise, stable, and robust mobility tracking framework is essential. Compared with self-tracking that relies only on mobility observations from onboard sensors [e.g., global positioning system (GPS), inertial measurement unit (IMU), and camera], cooperative tracking markedly increases the precision and reliability of the mobility information by integrating observations from roadside units (RSUs) and nearby vehicles through vehicle-to-everything (V2X) communications in the Internet of Vehicles (IoV). Nevertheless, cooperative tracking can be quite vulnerable if there are malicious users sending bogus observations in the cooperative network. In this article, we present a malicious user detection framework, which includes two sequential detection algorithms and a secure mobility data exchange and fusion model to detect and remove bogus mobility information and integrate proposed detection algorithms with previous data fusion algorithms, which secures the cooperative mobility tracking in AD, ITS. Simulations validate the effectiveness and robustness of the proposed framework under different types of attacks.

With the development of advanced information and communication technology, the Internet of Vehicles (IoV) has been designed to associate with implementing the Intelligent Transportation System (ITS). Meanwhile, the traditional centralized architecture of the cloud services no longer meets the increasing demand for data exchange in IoV. Moreover, the traditional centralized architecture for ITS is vulnerable to the single point of failure, and lack of flexibility due to its dependence on a trusted third party (TTP). The emergence of blockchain technology provides a potential direction to address these problems. However, there are still some problems existing in the construction of an efficient blockchain system in IoV. In this paper, we propose a resource management scheme that improves the performance of blockchain systems by efficiently allocating computing resources. A resource control method and a resource monitoring system are developed to cooperate with the system. The superiority of the proposed method is fully demonstrated by comparing it with the existing baseline method.

PurposeIn an intelligent transportation system (for short, ITS) environment, a vehicle’s motion is affected by the information in a large scale. The purpose of this paper is to study the integration effect of multiple vehicles’ delayed velocities on traffic flow.Design/methodology/approachThis paper constructed a new car-following model to study the integration effect of multiple vehicles’ delayed velocities on traffic flow. The new model is analyzed by linear and nonlinear perturbation method theoretically and also verified by simulation.FindingsIt is found out that the integration of preceding vehicles’ delayed velocities affect the stability of traffic flow importantly, and three preceding vehicles’ delayed velocities information should be considered in real traffic.Originality/valueThe new car-following model by considering the integration effect of multiple vehicles’ delayed velocities is firstly proposed in this paper. The research result shows that three preceding vehicles’ delayed velocities information is the best choice to stabilizing traffic flow.

With the incoming introduction of 5G networks and the advancement in technologies such as network function virtualization and software defined networking, new and emerging networking technologies and use cases are taking shape. One such technology is the Internet of Vehicles (IoV), which describes an interconnected system of vehicles and infrastructure. Coupled with recent developments in artificial intelligence and machine learning, IoV is transformed into an intelligent transportation system (ITS). There are, however, several operational considerations that hinder the adoption of ITSs, including scalability, high availability, and data privacy. To address these challenges, federated learning, a collaborative and distributed intelligence technique, is suggested. Through an ITS case study, the ability of a federated model deployed on roadside infrastructure throughout the network to recover from faults by leveraging group intelligence while reducing recovery time and restoring acceptable system performance is highlighted. With a multitude of use cases and benefits, federated learning is a key enabler for ITS and is poised to achieve widespread implementation in 5G and beyond networks and applications.

Nowadays, Internet of Vehicles (IoV) are considered as the most important promoter domain in the Intelligent Transportation System (ITS). Vehicles in IoV are characterized by a high nodes’ mobility, high nodes’ number and high data storage. However, IoV suffer from many challenges in order to achieve robust communication between vehicles such as frequent link disconnection, delay, and network overhead. In the traditional Vehicular Ad hoc NETworks (VANETs), these problems have often been solved by using clustering algorithms. Clustering in IoV can overcome and minimize the communication problems that face vehicles by reducing the network overhead and ensure some Quality of Service (QoS) to make network connectivity more stable. In this work, we propose a new Geo-graphical Information based Clustering Algorithm “GICA” destined to IoV environment. The proposal aims to maintain the cluster structure while respecting the quality of service requirements as the network evolves. We evaluated our proposed approach using the NS3 simulator and the realistic mobility model SUMO.