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

A Review of Research on Privacy Protection of Internet of Vehicles Based on Blockchain

Numerous academic and industrial fields, such as healthcare, banking, and supply chain management, are rapidly adopting and relying on blockchain technology. It has also been suggested for application in the internet of vehicles (IoV) ecosystem as a way to improve service availability and reliability. Blockchain offers decentralized, distributed and tamper-proof solutions that bring innovation to data sharing and management, but do not themselves protect privacy and data confidentiality. Therefore, solutions using blockchain technology must take user privacy concerns into account. This article reviews the proposed solutions that use blockchain technology to provide different vehicle services while overcoming the privacy leakage problem which inherently exists in blockchain and vehicle services. We analyze the key features and attributes of prior schemes and identify their contributions to provide a comprehensive and critical overview. In addition, we highlight prospective future research topics and present research problems

Secured information dissemination and misbehavior detection in VANETs

In a connected vehicle environment, the vehicles in a region can form a distributed network (Vehicular Ad-hoc Network or VANETs) where they can share traffic-related information such as congestion or no-congestion with other vehicles within its proximity, or with a centralized entity via. the roadside units (RSUs). However, false or fabricated information injected by an attacker (or a malicious vehicle) within the network can disrupt the decision-making process of surrounding vehicles or any traffic-monitoring system. Since in VANETs the size of the distributed network constituting the vehicles can be small, it is not difficult for an attacker to propagate an attack across multiple vehicles within the network. Under such circumstances, it is difficult for any traffic monitoring organization to recognize the traffic scenario of the region of interest (ROI). Furthermore, even if we are able to establish a secured connected vehicle environment, an attacker can leverage the connectivity of individual vehicles to the outside world to detect vulnerabilities, and disrupt the normal functioning of the in-vehicle networks of individual vehicles formed by the different sensors and actuators through remote injection attacks (such as Denial of Service (DoS)). Along this direction, the core contribution of our research is directed towards secured data dissemination, detection of malicious vehicles as well as false and fabricated information within the network. as well as securing the in-vehicle networks through improvisation of the existing arbitration mechanism which otherwise leads to Denial of Service (DoS) attacks (preventing legitimate components from exchanging messages in a timely manner). --Abstract, page iv

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

A Privacy-Preservation Framework based on Biometrics Blockchain (BBC) to Prevent Attacks in VANET

In the near future, intelligent vehicles will be part of the Internet of Things (IoT) and will offer valuable services and opportunities that could revolutionise human life in smart cities. The Vehicular Ad-hoc Network (VANET) is the core structure of intelligent vehicles. It ensures the accuracy and security of communication in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) modes to enhance road safety and decrease traffic congestion. However, VANET is subject to security vulnerabilities such as denial-of-service (DoS), replay attacks and Sybil attacks that may undermine the security and privacy of the network. Such issues may lead to the transmission of incorrect information from a malicious node to other nodes in the network. In this paper, we present a biometrics blockchain (BBC) framework to secure data sharing among vehicles in VANET and to retain statuary data in a conventional and trusted system. In the proposed framework, we take advantage of biometric information to keep a record of the genuine identity of the message sender, thus preserving privacy. Therefore, the proposed BBC scheme establishes security and trust between vehicles in VANET alongside the capacity to trace identities whenever required. Simulations in OMNeT++, veins and SUMO were carried out to demonstrate the viability of the proposed framework using the urban mobility model. The performance of the framework is evaluated in terms of packet delivery rate, packet loss rate and computational cost. The results show that our novel model is superior to existing approaches

A Double-Layer Blockchain Based Trust Management Model for Secure Internet of Vehicles

The Internet of Vehicles (IoV) enables vehicles to share data that help vehicles perceive the surrounding environment. However, vehicles can spread false information to other IoV nodes; this incorrect information misleads vehicles and causes confusion in traffic, therefore, a vehicular trust model is needed to check the trustworthiness of the message. To eliminate the spread of false information and detect malicious nodes, we propose a double-layer blockchain trust management (DLBTM) mechanism to objectively and accurately evaluate the trustworthiness of vehicle messages. The double-layer blockchain consists of the vehicle blockchain and the RSU blockchain. We also quantify the evaluation behavior of vehicles to show the trust value of the vehicle’s historical behavior. Our DLBTM uses logistic regression to accurately compute the trust value of vehicles, and then predict the probability of vehicles providing satisfactory service to other nodes in the next stage. The simulation results show that our DLBTM can effectively identify malicious nodes, and over time, the system can recognize at least 90% of malicious nodes

Achieving cybersecurity in blockchain-based systems: a survey

With The Increase In Connectivity, The Popularization Of Cloud Services, And The Rise Of The Internet Of Things (Iot), Decentralized Approaches For Trust Management Are Gaining Momentum. Since Blockchain Technologies Provide A Distributed Ledger, They Are Receiving Massive Attention From The Research Community In Different Application Fields. However, This Technology Does Not Provide With Cybersecurity By Itself. Thus, This Survey Aims To Provide With A Comprehensive Review Of Techniques And Elements That Have Been Proposed To Achieve Cybersecurity In Blockchain-Based Systems. The Analysis Is Intended To Target Area Researchers, Cybersecurity Specialists And Blockchain Developers. For This Purpose, We Analyze 272 Papers From 2013 To 2020 And 128 Industrial Applications. We Summarize The Lessons Learned And Identify Several Matters To Foster Further Research In This AreaThis work has been partially funded by MINECO, Spain grantsTIN2016-79095-C2-2-R (SMOG-DEV) and PID2019-111429RB-C21 (ODIO-COW); by CAM, Spain grants S2013/ICE-3095 (CIBERDINE),P2018/TCS-4566 (CYNAMON), co-funded by European Structural Funds (ESF and FEDER); by UC3M-CAM grant CAVTIONS-CM-UC3M; by the Excellence Program for University Researchers, Spain; and by Consejo Superior de Investigaciones Científicas (CSIC), Spain under the project LINKA20216 (“Advancing in cybersecurity technologies”, i-LINK+ program)