Blockchain Application on the Internet of Vehicles (IoV)

With the rapid development of the Internet of Things (IoT) and its potential integration with the traditional Vehicular Ad-Hoc Networks (VANETs), we have witnessed the emergence of the Internet of Vehicles (IoV), which promises to seamlessly integrate into smart transportation systems. However, the key characteristics of IoV, such as high-speed mobility and frequent disconnections make it difficult to manage its security and privacy. The Blockchain, as a distributed tamper-resistant ledge, has been proposed as an innovative solution that guarantees privacy-preserving yet secure schemes. In this paper, we review recent literature on the application of blockchain to IoV, in particular, and intelligent transportation systems in general

Location Privacy in VANETs: Improved Chaff-Based CMIX and Privacy-Preserving End-to-End Communication

VANETs communication systems are technologies and defined policies that can be formed to enable ITS applications to provide road traffic efficacy, warning about such issues as environmental dangers, journey circumstances, and in the provision of infotainment that considerably enhance transportation safety and quality. The entities in VANETs, generally vehicles, form part of a massive network known as the Internet of Vehicles (IoV). The deployment of large-scale VANETs systems is impossible without ensuring that such systems are themselves are safe and secure, protecting the privacy of their users. There is a risk that cars might be hacked, or their sensors become defective, causing inaccurate information to be sent across the network. Consequently, the activities and credentials of participating vehicles should be held responsible and quickly broadcast throughout a vast VANETs, considering the accountability in the system. The openness of wireless communication means that an observer can eavesdrop on vehicular communication and gain access or otherwise deduce users' sensitive information, and perhaps profile vehicles based on numerous factors such as tracing their travels and the identification of their home/work locations. In order to protect the system from malicious or compromised entities, as well as to preserve user privacy, the goal is to achieve communication security, i.e., keep users' identities hidden from both the outside world and the security infrastructure and service providers. Being held accountable while still maintaining one's privacy is a difficult balancing act. This thesis explores novel solution paths to the above challenges by investigating the impact of low-density messaging to improve the security of vehicle communications and accomplish unlinkability in VANETs. This is achieved by proposing an improved chaff-based CMIX protocol that uses fake messages to increase density to mitigate tracking in this scenario. Recently, Christian \etall \cite{vaas2018nowhere} proposed a Chaff-based CMIX scheme that sends fake messages under the presumption low-density conditions to enhance vehicle privacy and confuse attackers. To accomplish full unlinkability, we first show the following security and privacy vulnerabilities in the Christian \etall scheme: linkability attacks outside the CMIX may occur due to deterministic data-sharing during the authentication phase (e.g., duplicate certificates for each communication). Adversaries may inject fake certificates, which breaks Cuckoo Filters' (CFs) updates authenticity, and the injection may be deniable. CMIX symmetric key leakage outside the coverage may occur. We propose a VPKI-based protocol to mitigate these issues. First, we use a modified version of Wang \etall's \cite{wang2019practical} scheme to provide mutual authentication without revealing the real identity. To this end, a vehicle's messages are signed with a different pseudo-identity “certificate”. Furthermore, the density is increased via the sending of fake messages during low traffic periods to provide unlinkability outside the mix-zone. Second, unlike Christian \etall's scheme, we use the Adaptive Cuckoo Filter (ACF) instead of CF to overcome the effects of false positives on the whole filter. Moreover, to prevent any alteration of the ACFs, only RUSs distribute the updates, and they sign the new fingerprints. Third, mutual authentication prevents any leakage from the mix zones' symmetric keys by generating a fresh one for each communication through a Diffie–Hellman key exchange. As a second main contribution of this thesis, we focus on the V2V communication without the interference of a Trusted Third Party (TTP)s in case this has been corrupted, destroyed, or is out of range. This thesis presents a new and efficient end-to-end anonymous key exchange protocol based on Yang \etall's \cite{yang2015self} self-blindable signatures. In our protocol, vehicles first privately blind their own private certificates for each communication outside the mix-zone and then compute an anonymous shared key based on zero-knowledge proof of knowledge (PoK). The efficiency comes from the fact that once the signatures are verified, the ephemeral values in the PoK are also used to compute a shared key through an authenticated Diffie-Hellman key exchange protocol. Therefore, the protocol does not require any further external information to generate a shared key. Our protocol also does not require interfacing with the Roadside Units or Certificate Authorities, and hence can be securely run outside the mixed-zones. We demonstrate the security of our protocol in ideal/real simulation paradigms. Hence, our protocol achieves secure authentication, forward unlinkability, and accountability. Furthermore, the performance analysis shows that our protocol is more efficient in terms of computational and communications overheads compared to existing schemes.Kuwait Cultural Offic

A transparent distributed ledger-based certificate revocation scheme for VANETs

The widespread adoption of Cooperative, Connected, and Automated Mobility (CCAM) applications requires the implementation of stringent security mechanisms to minimize the surface of cyber attacks. Authentication is an effective process for validating user identity in vehicular networks. However, authentication alone is not enough to prevent dangerous attack situations. Existing security mechanisms are not able to promptly revoke the credentials of misbehaving vehicles, thus tolerate malicious actors to remain trusted in the system for a long time. The resulting vulnerability window allows the implementation of complex attacks, thus posing a substantial impairment to the security of the vehicular ecosystem. In this paper we propose a Distributed Ledger-based Vehicular Revocation Scheme that improves the state of the art by providing a vulnerability window lower than 1 s, reducing well-behaved vehicles exposure to sophisticated and potentially dangerous attacks. The proposed scheme harnesses the advantages of the underlying Distributed Ledger Technology (DLT) to implement a privacy-aware revocation process while being fully transparent to all participating entities. Furthermore, it meets the critical message processing times defined by EU and US standards, thus closing a critical gap in the current international standards. Theoretical analysis and experimental validation demonstrate the effectiveness and efficiency of the proposed scheme, where DLT streamlines the revocation operation overhead and delivers an economically viable yet scalable solution against cyber attacks on vehicular systems

A secured message transmission protocol for vehicular ad hoc networks

Vehicular Ad hoc Networks (VANETs) become a very crucial addition in the Intelligent Transportation System (ITS). It is challenging for a VANET system to provide security services and parallelly maintain high throughput by utilizing limited resources. To overcome these challenges, we propose a blockchain-based Secured Cluster-based MAC (SCB-MAC) protocol. The nearby vehicles heading towards the same direction will form a cluster and each of the clusters has its blockchain to store and distribute the safety messages. The message which contains emergency information and requires Strict Delay Requirement (SDR) for transmission are called safety messages (SM). Cluster Members (CMs) sign SMs with their private keys while sending them to the blockchain to confirm authentication, integrity, and confidentiality of the message. A Certificate Authority (CA) is responsible for physical verification, key generation, and privacy preservation of the vehicles. We implemented a test scenario as proof of concept and tested the safety message transmission (SMT) protocol in a real-world platform. Computational and storage overhead analysis shows that the proposed protocol for SMT implements security, authentication, integrity, robustness, non-repudiation, etc. while maintaining the SDR. Messages that are less important compared to the SMs are called non-safety messages (NSM) and vehicles use RTS/CTS mechanism for NSM transmission. Numerical studies show that the proposed NSM transmission method maintains 6 times more throughput, 2 times less delay and 125% less Packet Dropping Rate (PDR) than traditional MAC protocols. These results prove that the proposed protocol outperforms the traditionalMAC protocols

Blockchain-Enabled Federated Learning Approach for Vehicular Networks

Data from interconnected vehicles may contain sensitive information such as location, driving behavior, personal identifiers, etc. Without adequate safeguards, sharing this data jeopardizes data privacy and system security. The current centralized data-sharing paradigm in these systems raises particular concerns about data privacy. Recognizing these challenges, the shift towards decentralized interactions in technology, as echoed by the principles of Industry 5.0, becomes paramount. This work is closely aligned with these principles, emphasizing decentralized, human-centric, and secure technological interactions in an interconnected vehicular ecosystem. To embody this, we propose a practical approach that merges two emerging technologies: Federated Learning (FL) and Blockchain. The integration of these technologies enables the creation of a decentralized vehicular network. In this setting, vehicles can learn from each other without compromising privacy while also ensuring data integrity and accountability. Initial experiments show that compared to conventional decentralized federated learning techniques, our proposed approach significantly enhances the performance and security of vehicular networks. The system's accuracy stands at 91.92\%. While this may appear to be low in comparison to state-of-the-art federated learning models, our work is noteworthy because, unlike others, it was achieved in a malicious vehicle setting. Despite the challenging environment, our method maintains high accuracy, making it a competent solution for preserving data privacy in vehicular networks.Comment: 7 page

A secured privacy-preserving multi-level blockchain framework for cluster based VANET

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Existing research shows that Cluster-based Medium Access Control (CB-MAC) protocols perform well in controlling and managing Vehicular Ad hoc Network (VANET), but requires ensuring improved security and privacy preserving authentication mechanism. To this end, we propose a multi-level blockchain-based privacy-preserving authentication protocol. The paper thoroughly explains the formation of the authentication centers, vehicles registration, and key generation processes. In the proposed architecture, a global authentication center (GAC) is responsible for storing all vehicle information, while Local Authentication Center (LAC) maintains a blockchain to enable quick handover between internal clusters of vehicle. We also propose a modified control packet format of IEEE 802.11 standards to remove the shortcomings of the traditional MAC protocols. Moreover, cluster formation, membership and cluster-head selection, and merging and leaving processes are implemented while considering the safety and non-safety message transmission to increase the performance. All blockchain communication is performed using high speed 5G internet while encrypted information is transmitted while using the RSA-1024 digital signature algorithm for improved security, integrity, and confidentiality. Our proof-of-concept implements the authentication schema while considering multiple virtual machines. With detailed experiments, we show that the proposed method is more efficient in terms of time and storage when compared to the existing methods. Besides, numerical analysis shows that the proposed transmission protocols outperform traditional MAC and benchmark methods in terms of throughput, delay, and packet dropping rate

SPATA: Strong Pseudonym based AuthenTicAtion in Intelligent Transport System

Intelligent Transport System (ITS) is generally deployed to improve road safety, comfort, security, and traffic efficiency. A robust mechanism of authentication and secure communication is required to protect privacy and conditional resolution of pseudonyms to revoke malicious vehicles. In a typical ITS framework, a station can be a vehicle, Road Side Unit (RSU), or a server that can participate in communication. During authentication, the real identity of an Intelligent Transport System-Station (ITSS), referred to as a vehiclečň should not be revealed in order to preserve its privacy. In this paper, we propose a Strong Pseudonym based AutenTicAtion (SPATA) framework for preserving the real identity of vehicles. The distributed architecture of SPATA allows vehicles to generate pseudonyms in a very private and secure way. In the absence of a distributed architecture, the privacy cannot be preserved by storing information regarding vehicles in a single location. Therefore, the concept of linkability of certificates based on single authority is eliminated. This is done by keeping the real identity to pseudonym mappings distributed. Furthermore, the size of the Certificate Revocation List (CRL) is kept small, as only the most recent revoked communication pseudonyms are kept in the CRL. The privacy of the vehicle is preserved during the revocation and resolution phase through the distributed mechanism. Empirical results show that SPATA is a lightweight framework with low computational overhead, average latency, overhead ratio, and stable delivery ratio, in both sparse and dense network scenarios

A blockchain-based authentication protocol for cooperative vehicular ad hoc network

The efficiency of cooperative communication protocols to increase the reliability and range of transmission for Vehicular Ad hoc Network (VANET) is proven, but identity verification and communication security are required to be ensured. Though it is difficult to maintain strong network connections between vehicles because of there high mobility, with the help of cooperative communication, it is possible to increase the communication efficiency, minimise delay, packet loss, and Packet Dropping Rate (PDR). However, cooperating with unknown or unauthorized vehicles could result in information theft, privacy leakage, vulnerable to different security attacks, etc. In this paper, a blockchain based secure and privacy preserving authentication protocol is proposed for the Internet of Vehicles (IoV). Blockchain is utilized to store and manage the authentication information in a distributed and decentralized environment and developed on the Ethereum platform that uses a digital signature algorithm to ensure confidentiality, non-repudiation, integrity, and preserving the privacy of the IoVs. For optimized communication, transmitted services are categorized into emergency and optional services. Similarly, to optimize the performance of the authentication process, IoVs are categorized as emergency and general IoVs. The proposed cooperative protocol is validated by numerical analyses which show that the protocol successfully increases the system throughput and decreases PDR and delay. On the other hand, the authentication protocol requires minimum storage as well as generates low computational overhead that is suitable for the IoVs with limited computer resources

A Novel Identity-Based Privacy-Preserving Anonymous Authentication Scheme for Vehicle-to-Vehicle Communication

This paper proposes a novel bilinear pairing-free identity-based privacy-preserving anonymous authentication scheme for vehicle-to-vehicle (V2V) communication, called “NIBPA”. Today, vehicular ad hoc networks (VANETs) offer important solutions for traffic safety and efficiency. However, VANETs are vulnerable to cyberattacks due to their use of wireless communication. Therefore, authentication schemes are used to solve security and privacy issues in VANETs. The NIBPA satisfies the security and privacy requirements and is robust to cyberattacks. It is also a pairing-free elliptic curve cryptography (ECC)-based lightweight authentication scheme. The bilinear pairing operation and the map-to-point hash function in cryptography have not been used because of their high computational costs. Moreover, it provides batch message verification to improve VANETs performance. The NIBPA is compared to existing schemes in terms of computational cost and communication cost. It is also a test for security in the random oracle model (ROM). As a result of security and performance analysis, NIBPA gives better results compared to existing schemes

A Trust Management Framework for Vehicular Ad Hoc Networks

The inception of Vehicular Ad Hoc Networks (VANETs) provides an opportunity for road users and public infrastructure to share information that improves the operation of roads and the driver experience. However, such systems can be vulnerable to malicious external entities and legitimate users. Trust management is used to address attacks from legitimate users in accordance with a user’s trust score. Trust models evaluate messages to assign rewards or punishments. This can be used to influence a driver’s future behaviour or, in extremis, block the driver. With receiver-side schemes, various methods are used to evaluate trust including, reputation computation, neighbour recommendations, and storing historical information. However, they incur overhead and add a delay when deciding whether to accept or reject messages. In this thesis, we propose a novel Tamper-Proof Device (TPD) based trust framework for managing trust of multiple drivers at the sender side vehicle that updates trust, stores, and protects information from malicious tampering. The TPD also regulates, rewards, and punishes each specific driver, as required. Furthermore, the trust score determines the classes of message that a driver can access. Dissemination of feedback is only required when there is an attack (conflicting information). A Road-Side Unit (RSU) rules on a dispute, using either the sum of products of trust and feedback or official vehicle data if available. These “untrue attacks” are resolved by an RSU using collaboration, and then providing a fixed amount of reward and punishment, as appropriate. Repeated attacks are addressed by incremental punishments and potentially driver access-blocking when conditions are met. The lack of sophistication in this fixed RSU assessment scheme is then addressed by a novel fuzzy logic-based RSU approach. This determines a fairer level of reward and punishment based on the severity of incident, driver past behaviour, and RSU confidence. The fuzzy RSU controller assesses judgements in such a way as to encourage drivers to improve their behaviour. Although any driver can lie in any situation, we believe that trustworthy drivers are more likely to remain so, and vice versa. We capture this behaviour in a Markov chain model for the sender and reporter driver behaviours where a driver’s truthfulness is influenced by their trust score and trust state. For each trust state, the driver’s likelihood of lying or honesty is set by a probability distribution which is different for each state. This framework is analysed in Veins using various classes of vehicles under different traffic conditions. Results confirm that the framework operates effectively in the presence of untrue and inconsistent attacks. The correct functioning is confirmed with the system appropriately classifying incidents when clarifier vehicles send truthful feedback. The framework is also evaluated against a centralized reputation scheme and the results demonstrate that it outperforms the reputation approach in terms of reduced communication overhead and shorter response time. Next, we perform a set of experiments to evaluate the performance of the fuzzy assessment in Veins. The fuzzy and fixed RSU assessment schemes are compared, and the results show that the fuzzy scheme provides better overall driver behaviour. The Markov chain driver behaviour model is also examined when changing the initial trust score of all drivers