Asif Ali Laghari, Abdullah Ayub Khan, Reem Alkanhel, Hela Elmannai · 5 authors
The vast enhancement in the development of the Internet of Vehicles (IoV) is due to the impact of the distributed emerging technology and topology of the industrial IoV. It has created a new paradigm, such as the security-related resource constraints of Industry 5.0. A new revolution and dimension in the IoV popup raise various critical challenges in the existing information preservation, especially in node transactions and communication, transmission, trust and privacy, and security-protection-related problems, which have been analyzed. These aspects pose serious problems for the industry to provide vehicular-related data integrity, availability, information exchange reliability, provenance, and trustworthiness for the overall activities and service delivery prospects against the increasing number of multiple transactions. In addition, there has been a lot of research interest that intersects with blockchain and Internet of Vehicles association. In this regard, the inadequate performance of the Internet of Vehicles and connected nodes and the high resource requirements of the consortium blockchain ledger have not yet been tackled with a complete solution. The introduction of the NuCypher Re-encryption infrastructure, hashing tree and allocation, and blockchain proof-of-work require more computational power as well. This paper contributes in two different folds. First, it proposes a blockchain sawtooth-enabled modular architecture for protected, secure, and trusted execution, service delivery, and acknowledgment with immutable ledger storage and security and peer-to-peer (P2P) network on-chain and off-chain inter-communication for vehicular activities. Secondly, we design and create a smart contract-enabled data structure in order to provide smooth industrial node streamlined transactions and broadcast content. Substantially, we develop and deploy a hyperledger sawtooth-aware customized consensus for multiple proof-of-work investigations. For validation purposes, we simulate the exchange of information and related details between connected devices on the IoV. The simulation results show that the proposed architecture of BIoV reduces the cost of computational power down to 37.21% and the robust node generation and exchange up to 56.33%. Therefore, only 41.93% and 47.31% of the Internet of Vehicles-related resources and network constraints are kept and used, respectively.
With the continuous development of communication technology, drones are playing an important role in many fields, such as power transmission line inspection and agricultural pesticide spraying. In order to protect the data privacy and communication security of drones, many experts are considering blockchain as its enabling technology. However, due to their small size and limited power storage, drones cannot support energy-intensive blockchain applications. In addition, the future 6G communications need to implement an important key performance indicator, namely extremely low-power communications (ELPCs). As a consequence, research into green blockchain is becoming more and more popular. The broadcast of the blockchain is one of the most energy-intensive parts because it entails flooding and there are a lot of unnecessary communication processes. Therefore, in order to make blockchain more suitable for ELPC requirements in 6G communications and unmanned aerial vehicle (UAV) networks, we took the blockchain broadcast as an improvement candidate and designed LECast, a low-energy-consumption protocol. LECast first analyzes the energy consumption model of the communication between two drones and constructs the shortest-path broadcast tree (SPB Tree) for the UAV networks to minimize energy consumption. Meanwhile, to make the sending drone address the receiving drone in a more convenient way, we proposed an extended Huffman coding (EHC) scheme to name the drones. Furthermore, the other issues with the broadcast tree are reliability and security. When a channel fails, subsequent drones cannot smoothly receive the transaction or block data. As a result, we introduced multichannel transmission with splitting data (MTSD); that is, the transaction or block data are divided into segments and transmitted in parallel multiple times over multiple channels. Finally, through the analysis and simulation of LECast in terms of energy consumption, latency, throughput, reliability, security, and coverage rate, the advantages of LECast were confirmed, which could meet the requirements of ELPCs and be well applied to UAV networks.
Abstract The Internet of Vehicles (IoV) is the next phase in the evolution of vehicular ad hoc networks (VANETs).Multiple types of Smart Networks exists in our surrounding.i.e., Wireless Sensor Networks (WSNs), Crowd Sensing Networks (CSNs), and Internet of Vehicles, etc A VANET is a collection of mobile nodes (vehicles) that share data through ad hoc on-demand connections. Vehicle Tracking is one of the uses of IOV(Internet of Vehicles) and Vehicle Security is one of the major issues for all vehicle owners. On a vehicle, there are various on-board sensors that sense a vehicle’s motion and the surrounding environment. On-board sensors can also warn drivers about approaching vehicles, speeding, and slippery road conditions. The main aim of the paper is to provide solutions for False Data Injection Attack by Integration of Blockchain Based IPFS-Trust Management System with ML SVR Regression Model. Due to Network Assaults and Threats under Vanet System, the safety of the drivers is under stake and Critical. A rogue node can send out erroneous messages, causing unavoidable scenarios. We first filter the received data from Vehicles creating false traffic jam warning messages using the Machine learning SVR Regression Model where data is created and split into train and test data. We used Machine learning supervised algorithm to find whether the vehicle is a legitimate vehicle or an attacker vehicle and the result is validated using the parameters like Accuracy, Loss Rate, Precision, Recall, and F-Test Score. Algorithm Implementation results show that the FDIA attack strategy achieves a better performance than the without using ML algorithm of SVR Regression Model based attack strategy in Predicting the Vanet Security. Also, we studied the various ways to mitigate the impact of false data injection into the network through a compromised node. Users can access the system through DApp, an Ethereum-distributed application, and manage their vehicle data.
Mahmoud A. Shawky, Abdul Jabbar, Muhammad Usman, Muhammad Ali Imran · 7 authors
This letter proposes a group key distribution scheme using smart contract-based blockchain technology. The smart contract’s functions allow for securely distributing the group session key, following the initial legitimacy detection using public key infrastructure-based authentication. For message authentication, we propose a lightweight symmetric key cryptography-based group signature method, supporting the security and privacy requirements of vehicular ad hoc networks (VANETs). Our discussion examined the scheme’s robustness against typical adversarial attacks. To evaluate the gas costs associated with smart contracts functions, we implemented it on the Ethereum main network. Finally, comprehensive analyses of computation and communication costs demonstrate the scheme’s effectiveness.
Internet of Vehicles (IoV) has become an indispensable technology to bridge vehicles, persons, and infrastructures and is promising to make our cities smarter and more connected. It enables vehicles to exchange vehicular data (e.g., GPS, sensors, and brakes) with different entities nearby. However, sharing these vehicular data over the air raises concerns about identity privacy leakage. Besides, the centralized architecture adopted in existing IoV systems is fragile to single point-of-failure and malicious attacks. With the emergence of blockchain technology, there is the chance to solve these problems due to its features of being tamper-proof, traceability, and decentralization. In this article, we propose a privacy-preserving vehicular data sharing framework based on blockchain. In particular, we design an anonymous and auditable data sharing scheme using Zero-Knowledge Proof (ZKP) technology so as to protect the identity privacy of vehicles while preserving the vehicular data auditability for Trusted Authorities (TAs). In response to high mobility of vehicles, we design an efficient multi-sharding protocol to decrease blockchain communication costs without compromising the blockchain security. We implement a prototype of our framework and conduct extensive experiments and simulations on it. Evaluation and analysis results indicate that our framework can not only strengthen system security and data privacy but also reduce communication complexity by \(O(\frac{n\sqrt {m}}{m^2})\) times compared to existing sharding protocols.
With the increasing number of vehicles connected to the Internet of Vehicles (IoV), to accommodate the evolving needs and patterns of new vehicles, passengers, and drivers, traditional single Trusted Authority (TA) authentication model may no longer be suitable for the IoV scenario, it is crucial to develop secure, lightweight, efficient, and cross-TA identity authentication and key agreement algorithms. In 2021, Xu et al. proposed a blockchain-based Roadside Unit (RSU)-assisted authentication and key agreement protocol for IoV. However, we describe that their protocol is vulnerable to identity guessing attacks, vehicle forgery attacks, and lacks of session key security and known session key secrecy, and propose a novel blockchain and elliptic curve cryptography-based cross-TA authentication and key agreement protocol for IoV. Our protocol uses Physical Unclonable Functions (PUF) and biometric keys to resist RSU capture attacks and Onboard Unit (OBU) intrusion attacks. Formal security proof and comparative analysis indicate that the proposed protocol can resist various known attacks and maintains lower computational complexity.
Vehicular adhoc networks (VANETs) are an interesting area of exploration among the intelligent transportation research community.Communication among vehicles with infrastructure units is an essential component.Thus, trust and privacy are important concerns in addition to dynamic topology, which is the main characteristic of VANETs.Ensuring the vehicles do not broadcast false information as well as protecting the identity of vehicles against tracking attacks are the objectives of this article.Here, a blockchain-based solution has been proposed to establish an identity-preserving trust model for VANETs.It preserves the real identities of vehicles with the utilization of Ethereum blockchain technology.A trust evaluation algorithm has been implemented to stop the dissemination of fraudulent messages.Validation of the algorithm has been conducted by running the algorithm in different VANET scenarios.
In the fire scene investigation, the firefighting Internet of Things (IoT) data is the key electronic evidence for event analysis and responsibility determination. However, the traditional centralized storage method leads to data easy to be tampered with and damaged. To solve these problems, this paper designs and implements a secure, reliable and low-cost distributed firefighting IoT data storage scheme based on the Fabric framework, combining blockchain technology, Interplanetary File System (IPFS) and Practical Byzantine Fault Tolerance (PBFT) consensus algorithm to provide a strong support for fire accident traceability. This scheme mainly includes the storage model, key algorithms and Fabric construction and improvement. IPFS stores the complete firefighting IoT data, as the off-chain storage system of the blockchain, and the blockchain only stores the storage address (IPFS hash) of data returned by IPFS, thus reducing the storage space overhead of the blockchain and ensuring data security. Further, we adopt the Fabric framework as the blockchain platform for firefighting IoT data, and embed the PBFT consensus algorithm into the framework to ensure the reliability of consensus nodes in Fabric, thus improving the availability of the blockchain. In addition, we use the AES and RSA algorithms to ensure the security of firefighting IoT data storage and transmission. Through system analysis and experimental testing, the proposed scheme meets the need for secure storage and traceability of firefighting IoT data. Compared with the storage scheme using only blockchain, the blockchain combined with IPFS technology has advantages in storage space occupation, significantly improved throughput, and lower latency overhead. Meanwhile, compared with the official Fabric, the improved Fabric supports Byzantine fault tolerance and has better security.
Patruni Muralidhara Rao, Srinivas Jangirala, P. Vidhya Saraswathi, Ashok Kumar Das · 5 authors
In V2X (vehicle-to-everything) communication, there is a two-way communication among the vehicle(s) and other Internet of Things (IoT)-enabled smart devices around it that may change how we need to drive. Due to the advancement of Information and Communications Technology (ICT) and the rapid development of IoT in transportation, traditional applications are converted to intelligent applications. In V2X communications, the collected information from the IoT smart devices and other sources passes through low-latency, high-bandwidth, high-reliability links. With the future adoption of the 5th generation mobile network (5G) and beyond networks, V2X continues to produce a huge volume of data. However, collecting and storing data securely in blockchain-based storage are extremely needed for immutability and transparency. In this survey article, the convergence of IoT, V2X and blockchain technologies, and various security challenges and their countermeasures are discussed. Next, we discuss various V2X applications and their respective services. Moreover, IoT-V2X architecture and its enabling technologies are discussed in this article. In addition, we also provide a comprehensive analysis of various security mechanisms. Finally, we provide some important challenges and issues of Blockchain for Intelligent Transportation System (BITS).
Unmanned-aerial-vehicle (UAV)-enabled intelligent transportation system (ITS) is an advanced technology that can provide various services including autonomous driving, real-time creation of high-definition maps, and car sharing. In particular, a UAV-enabled ITS can be realized through the combination of traditional vehicular ad hoc networks (VANETs) and UAVs that can act as flying roadside units (RSUs) at the outskirts and monitor road conditions from predefined locations to spot car accidents and any law violations. Notably, to realize these services, real-time communication between UAVs and RSUs must be guaranteed. However, UAVs have limited computing powers, and if extensive computation is required during communication, the provision of real-time ITS services may be hindered. Furthermore, UAVs and RSUs communicate via public channels that are prone to various attacks, such as replay, impersonation, trace, and session key disclosure attacks. Thus, in this article, a secure and lightweight authentication scheme is proposed for UAVs and RSUs using the blockchain technology. The proposed scheme is analyzed using informal and formal methods including Burrows–Abadi–Nikoogadam (BAN) logic, automated validation of internet security protocols and applications (AVISPA) simulation tool, and real–or–random (RoR) model, and its performance is compared with that of related schemes. The results reveal that the proposed scheme is more efficient and secure as compared to the other competing schemes.
Sulaiman M. Karim, Adib Habbal, Shehzad Ashraf Chaudhry, Azeem Irshad
The Internet of Vehicles (IoV) is a network that connects vehicles and their environment: in-built devices, pedestrians, and infrastructure through the Internet using heterogeneous access technologies. During communication between vehicles, roadside units, and control rooms, data confidentiality and privacy are critical issues that require effective measures. Several works have been proposed for securing IoV environments based on vehicles-to-infrastructure authentication; However, some schemes have security vulnerabilities, while others have shown efficiency issues. Due to its decentralization, stability, and transaction tracking capabilities, Blockchain as an emerging technology presents a potential solution for IoV security. This article provides an in-depth examination of the benefits of blockchain for a 5G-based IoV environment. In particular, we propose and evaluate a novel blockchain-based secure data exchange (BSDCE-IoV) scheme based on Elliptic Curve Cryptography algorithm. Our solution is designed to eliminate several potential attacks that pose a threat to the IoV environment. Deep examination using the Real-or-Random oracle model and Scyther tool, in addition to the informal security analysis, validates the scheme regarding security and privacy. The Multi-precision Integer and Rational Arithmetic Cryptographic Library (MIRACL) assesses the computational and communication overhead. Computational and communicative overheads were also evaluated using the Multi-precision Integer and Rational Arithmetic Cryptographic Library (MIRACL). BSDCE-IoV shows higher performance in terms of security, functionality, and time delay than a number of recent selective work in IoV security.
Internet of Vehicular Things (IoVT), as a subset of the Internet of Things (IoT), enhances safety, traffic management, and driver experience by connecting vehicles and facilitating data exchange. Indeed, the implementation of IoVT comes with its fair share of challenges, which include transparent and secure service management, security, privacy preservation, and prevention of malware attacks. Researchers have proposed reputation-based systems, including blockchain-supported ones, as effective solutions to address the challenges in IoVT, offering benefits such as integrity, authenticity, transparency, and privacy preservation support. On the other hand, cryptocurrency offers several advantages, such as decentralization, enhanced security, and lower transaction costs, making it an effective form of payment that can bypass traditional intermediaries and facilitate fast and borderless transactions with greater financial privacy and control for users. In this paper, a blockchain-based reputation management system is proposed that can collect information about the surroundings from intelligent vehicles, convert that data into appropriate information, and make necessary decisions regarding reported incidents. A cryptocurrency-based recovery system allows defaulters to recover their missing points through the use of digital tokens or assets, providing them with a transparent and decentralized mechanism for restoring their lost value or reputation. The proposed method for the cryptocurrency-based recovery system is implemented and tested using virtual machines, specifically utilizing the Ethereum blockchain and smart contract programming as proof of concept to showcase the functionality and feasibility of the system. Additionally, the packet structure and the throughput are also demonstrated to prove the efficiency of the proposed method.
Distributed deep learning (DDL) within vehicular ad hoc networks (VANETs) holds profound significance in developing smart applications, such as intelligent transport systems and autonomous driving, where multiple parties are coordinated to leverage the training capability and acquisitive intelligence. Blockchain (BC) is a distribution technology promising for trustworthy DDL, holding the divide-and-conquer concept with decentralized management and consensus algorithms to reduce the exposure of sensitive controllers and thus the risks of malicious system-wide attacks. Moreover, zero trust architecture (ZTA) concepts are promoted as innovative cybersecurity solution which can be integrated with BC to address the resource-limited and infrastructure-less issues to augment the strength of DDL in VANETs. In this dissertation, the BC and ZTA potential is explored to construct reliable VANETs for trustworthy data sharing and thus to support significant within-VANET DDL and relevant applications. Firstly, virtualized distributed ledger technology (vDLT) is developed as the multimedia BC platform, followed by vDLT-based VANETs built to solve the unsteady communication; secondly, vDLT is improved to transmit and secure traffic events in VANETs; subsequently, a vDLT-based DDL system is proposed to enhance object detection (OD) inside VANETs; finally, ZTA and sharding scheme are enabled in vDLT-based VANETs for improved protection. Generally, vDLT runs with virtualized resource and sharding supports for scalability improvement, along with multi-layered consensus algorithm and an adaptable hierarchical and decentralized PBAC (hdPBAC) access control model to agilely protect the DDL procedures and relevant DDL-related applications. The proposed system has been developed, including the vDLT system, the multimedia streaming over vDLT in fixed networks and VANETs, a precursory vDLT-based DDL system for OD purpose, and the integration of ZTA into scalable-BC-based VANETs. The evaluation results show the feasibility of proposed design and demonstrate the significance of performance improvements.
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.
Muhammad Firdaus, Harashta Tatimma Larasati, Kyung-Hyune Rhee
The enormous volume of heterogeneous data from various smart device-based applications has growingly increased a deeply interlaced cyber-physical system. In order to deliver smart cloud services that require low latency with strong computational processing capabilities, the Edge Intelligence System (EIS) idea is now being employed, which takes advantage of Artificial Intelligence (AI) and Edge Computing Technology (ECT). Thus, EIS presents a potential approach to enforcing future Intelligent Transportation Systems (ITS), particularly within a context of a Vehicular Network (VNets). However, the current EIS framework meets some issues and is conceivably vulnerable to multiple adversarial attacks because the central aggregator server handles the entire system orchestration. Hence, this paper introduces the concept of distributed edge intelligence, combining the advantages of Federated Learning (FL), Differential Privacy (DP), and blockchain to address the issues raised earlier. By performing decentralized data management and storing transactions in immutable distributed ledger networks, the blockchain-assisted FL method improves user privacy and boosts traffic prediction accuracy. Additionally, DP is utilized in defending the user’s private data from various threats and is given the authority to bolster the confidentiality of data-sharing transactions. Our model has been deployed in two strategies: First, DP-based FL to strengthen user privacy by masking the intermediate data during model uploading. Second, blockchain-based FL to effectively construct secure and decentralized traffic management in vehicular networks. The simulation results demonstrated that our framework yields several benefits for VNets privacy protection by forming a distributed EIS with privacy budget (ε) of 4.03, 1.18, and 0.522, achieving model accuracy of 95.8%, 93.78%, and 89.31%, respectively.
Federated learning (FL) is a distributed machine learning technique that allows multiple devices (e.g., smartphones and IoT devices) to collaborate in the training of a shared model with each device preserving the privacy of its local data. However, the highly heterogeneous distribution of data among clients in FL can result in poor convergence. In addressing this issue, the concept of personalized federated learning (PFL) has emerged. PFL aims to tackle the effects of non-independent and identically distributed data and statistical heterogeneity and to achieve personalized models with rapid model convergence. One approach is clustering-based PFL, which utilizes group-level client relationships to achieve personalization. However, this method still relies on a centralized approach, whereby the server coordinates all processes. To address these shortcomings, this study introduces a blockchain-enabled distributed edge cluster for PFL (BPFL) that combines the benefits of blockchain and edge computing. Blockchain technology can be used to enhance client privacy and security by recording transactions on immutable distributed ledger networks, thereby improving client selection and clustering. The edge computing system offers reliable storage and computation such that computational processing is locally performed in the edge infrastructure to be closer to clients. Thus, the real-time services and low-latency communication of PFL are improved. However, further work is required to develop a representative dataset for the examination of related types of attacks and defenses for a robust BPFL protocol.
Sana Hafeez, Ahsan Raza Khan, Mohammad Al-Quraan, Lina Mohjazi · 7 authors
Unmanned aerial vehicles (UAVs) have recently established their capacity to provide cost-effective and credible solutions for various real-world scenarios. UAVs provide an immense variety of services due to their autonomy, mobility, adaptability, and communications interoperability. Despite the expansive use of UAVs to support ground communications, data exchanges in those networks are susceptible to security threats because most communication is through radio or Wi-Fi signals, which are easy to hack. While several techniques exist to protect against cyberattacks. Recently emerging technology blockchain could be one of promising ways to enhance data security and user privacy in peer-to-peer UAV networks. Borrowing the superiorities of blockchain, multiple entities can communicate securely, decentralized, and equitably. This article comprehensively overviews privacy and security integration in blockchain-assisted UAV communication. For this goal, we present a set of fundamental analyses and critical requirements that can help build privacy and security models for blockchain and help manage and support decentralized data storage systems. The UAV communication system's security requirements and objectives, including availability, authentication, authorization, confidentiality, integrity, privacy, and non-repudiation, are thoroughly examined to provide a deeper insight. We wrap up with a discussion of open research challenges, the constraints of current UAV standards, and potential future research directions.
Ye Tao, Ehsan Javanmardi, Pengfei Lin, Jin Nakazato · 7 authors
Cooperative perception is crucial for connected automated vehicles in intelligent transportation systems (ITSs); however, ensuring the authenticity of perception data remains a challenge as the vehicles cannot verify events that they do not witness independently. Various studies have been conducted on establishing the authenticity of data, such as trust-based statistical methods and plausibility-based methods. However, these methods are limited as they require prior knowledge such as previous sender behaviors or predefined rules to evaluate the authenticity. To overcome this limitation, this study proposes a novel approach called zero-knowledge Proof of Traffic (zk-PoT), which involves generating cryptographic proofs to the traffic observations. Multiple independent proofs regarding the same vehicle can be deterministically cross-verified by any receivers without relying on ground truth, probabilistic, or plausibility evaluations. Additionally, no private information is compromised during the entire procedure. A full on-board unit software stack that reflects the behavior of zk-PoT is implemented within a specifically designed simulator called Flowsim. A comprehensive experimental analysis is then conducted using synthesized city-scale simulations, which demonstrates that zk-PoT’s cross-verification ratio ranges between 80 % to 96 %, and 90 % of the verification is achieved in 5 s, with a protocol overhead of approximately 25 %. Furthermore, the analyses of various attacks indicate that most of the attacks could be prevented, and some, such as collusion attacks, can be mitigated. The proposed approach can be incorporated into existing works, including the European Telecommunications Standards Institute (ETSI) and the International Organization for Standardization (ISO) ITS standards, without disrupting the backward compatibility.
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Privacy-Preserving Technologies in Data
Vehicular Ad Hoc Networks (VANETs)
Advanced Steganography and Watermarking Techniques
In vehicular ad hoc networks (VANET), the cross-domain identity authentication of users is very important for the development of VANET due to the large cross-domain mobility of vehicle users. The Public Key Infrastructure (PKI) system is often used to solve the identity authentication and security trust problems faced by VANET. However, the PKI system has challenges such as too centralized Authority of Certification Authority (CA), frequent cross-domain access to certificate interactions and high authentication volume, leading to high certificate management costs, complex cross-domain authentication paths, easy privacy leakage, and overburdened networks. To address these problems, this paper proposes a lightweight blockchain-based PKI identity management and authentication architecture that uses smart contracts to reduce the heavy burden caused by CAs directly managing the life cycle of digital certificates. On this basis, a trust chain based on smart contracts is designed to replace the traditional CA trust chain to meet the general cross-domain requirements, to effectively avoid the communication pressure caused by a mass of certificate transmissions. For the cross-domain scenario with higher privacy and security requirements the identity attribute authentication service is provided directly while protecting privacy by using the Merkle tree to anchor identity attribute data on and off the blockchain chain. Finally, the proposed scheme was comprehensively analyzed in terms of cost, time consumption and security.
Abstract Intelligent and networked vehicles help build an efficient vehicular network's infrastructure. The widespread use of electronic software exposes these networks to cyber‐attacks. Intrusion detection systems (IDS) are useful for preventing vehicle network assaults. IDS have been customized using machine and deep learning networks for greater real‐time performance. Current learning‐based intrusion detection systems demand substantial processing capabilities to train and update intricate training models in vehicular devices, resulting in decreased efficiency and ability to defend against assaults. This study presents Blockchain‐based Multi‐Layer Federated Extreme Learning Machines (MLFEM) enabled IDS (BEF‐IDS) for safe data transfers. The proposed IDS leverages federated learning to generate Multi‐Layered Extreme Learning Machines, which are offloaded to dispersed vehicular edge devices such as Road‐Side Units (RSU) and connected vehicles. This federated strategy decreases resource use without sacrificing security. Blockchain technology records and shares training models, assuring network security. Using real‐time data sets, the suggested algorithm's performance under different attack scenarios were extensively tested. The suggested method obtained 98% accuracy and Recall, 97.9% Precision, and 97.9% F1 Score performance, which suggests it's incredibly secure and costs very little to transmit.
Vehicular Ad-hoc Networks (VANETs) have a lot of potential for improving traffic management and driver safety. However, employing a wireless channel for vehicle communication has security and privacy concerns such as authentication, confidentiality, integrity, access control, and availability. Hence, it is indispensable to address the security and privacy aspects of the vehicles utilized in these contexts. In this study, a blockchain-based physically secure, and privacy-aware anonymous authentication technique leveraging the fog computing architecture. The proposed method can efficiently solve security and privacy problems using its attributes of support to movement, reduced latency, and location monitoring. In addition, the decentralized nature of blockchain technology is used to ensure the data security of vehicles. The vehicle is not required to store the secret keys to do anonymous authentication and provides physical security for the vehicle. The implied scheme provides essential security features with less storage, computational and communication costs than related competitive schemes.
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.