Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 2640 2023-12-07 22:49:17 |
2 update references and layout Meta information modification 2640 2023-12-08 02:23:01 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Juárez, R.; Bordel, B. Vehicular Ad Hoc Network. Encyclopedia. Available online: https://encyclopedia.pub/entry/52506 (accessed on 13 June 2024).
Juárez R, Bordel B. Vehicular Ad Hoc Network. Encyclopedia. Available at: https://encyclopedia.pub/entry/52506. Accessed June 13, 2024.
Juárez, Rubén, Borja Bordel. "Vehicular Ad Hoc Network" Encyclopedia, https://encyclopedia.pub/entry/52506 (accessed June 13, 2024).
Juárez, R., & Bordel, B. (2023, December 07). Vehicular Ad Hoc Network. In Encyclopedia. https://encyclopedia.pub/entry/52506
Juárez, Rubén and Borja Bordel. "Vehicular Ad Hoc Network." Encyclopedia. Web. 07 December, 2023.
Vehicular Ad Hoc Network
Edit

Vehicular ad hoc networks (VANETs), which are integral to the infrastructure of intelligent transport systems, facilitate the critical exchange of information between vehicular nodes.

vehicular ad hoc networks (VANETs) blockchain network threat mitigation

1. Introduction

The Internet of Vehicles (IoVs) represents an emerging application scenario for Internet of Things (IoTs) technology. At the heart of this technological evolution are vehicular ad hoc networks (VANETs), which facilitate communication between vehicles and between vehicles and infrastructures, thus constituting a key subset of the IoVs. VANETs have emerged as one of the most exciting research fields within intelligent transport systems, thereby providing safety and convenience information for drivers [1]. These networks can communicate the complex and dynamic data generated by vehicles, humans, and the environment in real time, such as traffic conditions, traffic accidents, road construction, and congestion. However, VANETs are especially vulnerable to a variety of security threats, including malicious attacks and the distribution of unreliable information, which can have severe consequences, such as traffic accidents.
Additionally, the distinct characteristics of VANETs introduce significant challenges in terms of security management, privacy, and reliability in their design [2][3]. So, creating an efficient anonymous authentication system with low computational cost [4] in a vehicular ad hoc network (VANET) represents a considerable challenge [5].
Specifically, in the realm of vehicular ad hoc networks (VANETs), the development of an efficient anonymous authentication system that maintains low computational costs poses significant challenges due to several intrinsic characteristics of these networks:
  • High Vehicle Mobility: The highly dynamic nature of VANETs, which are characterized by vehicles moving at high speeds, results in frequent changes in network nodes. This demands an authentication system that is capable of rapidly adapting to changes in network topology without compromising on security or performance.
  • Resource Limitations in Vehicles: Despite being equipped with advanced technologies, modern vehicles still face limitations in terms of processing power and storage capacity. An efficient authentication system must operate within these resource constraints, thereby ensuring light computational loads.
  • Anonymity and Privacy Needs: Given the sensitive nature of vehicular data, such as location and movement patterns, ensuring user anonymity and privacy is paramount. Achieving this without significantly increasing the computational burden adds complexity to system design.
  • Diversity and Scalability: VANETs support a wide array of applications, from road safety to infotainment services, each with its unique security requirements. The authentication system must be versatile enough to cater to these diverse needs and scalable to handle the increasing number of connected vehicles.
  • Resistance to Attacks and Frauds: Authentication systems in VANETs must be robust against various security threats, including impersonation attacks, Sybil attacks, and data manipulation. Designing a system that can effectively counter these threats without imposing excessive computational demands is a significant challenge.
For these reasons, developing an efficient and low-cost computational anonymous authentication system for VANETs is not only crucial for ensuring security and privacy within these networks, but also poses substantial technical challenges. The research aims to address these challenges through an innovative approach that balances security, efficiency, and practicality.
On the other hand, the incorporation of blockchain technology in VANETs presents a paradigm shift from traditional centralized systems to a more resilient, transparent, and decentralized framework. The blockchain, known for its immutable and secure ledger, is leveraged to enhance the tracking and verification of vehicular movements and interactions. This technology has shown promise in mitigating the inherent vulnerabilities of VANETs, thereby providing a robust platform for secure vehicular communication.
With the growing adoption of blockchain technology across various sectors, including transportation [6], this technology has also shown promise in resolving the challenges within VANETs. Blockchain technology provides a decentralized, secure, and trustworthy database maintained by network nodes [7][8]. In this way, it can be used to track, organize, and verify interactions among vehicles in the network.
In addition, blockchain technology can be also employed for securization purposes.
Cybersecurity threats to vehicular ad hoc networks (VANETs) have escalated in recent years, primarily due to their critical role in managing sensitive vehicular data [9]. The conventional centralized systems, typically operated by vehicle service providers, have demonstrated several security shortcomings. These systems often fail to offer the robust defense mechanisms necessary to protect against sophisticated cyberthreats, thus resulting in notable vulnerabilities within vehicular networks [10].
Additionally, the proliferation of wireless connected devices has exponentially increased the complexity of ensuring secure vehicular communications [11]. The intricate web of data exchange within VANETs demands a security solution that transcends the capabilities of traditional centralized systems. Herein lies the potential of blockchain technology—it offers a decentralized approach that inherently enhances the security, performance, and scalability of VANETs [12].
Blockchain technology’s application in VANETs extends beyond mere communication security [13][14]. It revolutionizes the entire ecosystem by enabling immutable record-keeping for vehicular history, thereby ensuring data integrity and fostering a transparent environment for data exchange. This immutable nature of blockchain technology is particularly pivotal, as it ensures that once vehicle data are recorded on the ledger, they cannot be altered or tampered with, thereby instilling trust in the vehicular data records [15].
In most prior approaches, vehicle security in VANETs was accomplished each time it entered the territory of a roadside unit (RSU). Relying solely on a single RSU presents a multitude of challenges. Firstly, it can become a performance bottleneck, especially in high-density areas where numerous vehicles might be entering or exiting simultaneously, thereby leading to latency in certification processes. Secondly, a solitary RSU becomes a single point of failure; if it malfunctions or becomes compromised, it can disrupt the certification of all the vehicles under its jurisdiction. This can also lead to potential security vulnerabilities, where malicious entities might target the RSU to either gain unauthorized access or to disrupt normal operations. Furthermore, there is an inherent lack of redundancy, meaning that if one RSU is down or is facing technical glitches, there is not an immediate backup system in place to continue the vehicle certification.
Integrating blockchain technology can alleviate some of these concerns [16][17]. The decentralized nature of the blockchain ensures that no single point of failure exists, thereby enhancing the robustness and resilience of the system [18]. Every transaction, in this case, vehicle certifications, can be recorded on the blockchain, thus making the data tamper-proof and ensuring its integrity. Moreover, the blockchain’s consensus mechanisms can be leveraged to validate vehicle entries, thereby reducing the burden on a single RSU and distributing the task across multiple nodes or participants in the network. This not only streamlines the certification process, but also introduces an added layer of security, thus making it exceedingly difficult for malicious actors to compromise the system.
In other words, the transition from traditional centralized systems to blockchain-based solutions equips VANETs with enhanced resilience against data breaches and unauthorized access. The decentralized nature of the blockchain mitigates the risk of single points of failure, which are inherent in centralized systems. Moreover, the blockchain empowers all network participants to engage in the maintenance of the ledger, thereby promoting a transparent and tamper-proof ecosystem [19].
In essence, the blockchain stands as a vanguard technology that propels VANETs into a new era of security and reliability. It ensures that vehicular communications are not only secure, but that they also conducted within a framework that is inherently resistant to cyber attacks. By integrating blockchain solutions, VANETs evolve into more resilient, transparent, and decentralized networks that are capable of withstanding the escalating threats in today’s cybersecurity landscape [20].

2. Blockchain Solutions for VANETs, Trust Models, Cyber Attacks, and Mitigation Strategies

Vehicular ad hoc networks (VANETs) are a specific form of mobile ad hoc networks (MANETs) that connect vehicles on the move. The main goal of VANETs is to provide road safety, traffic management, and various infotainment services. Due to the critical nature of these services, data security, privacy, and reliable communication are of paramount importance. However, the highly dynamic and distributed nature of VANETs presents unique challenges to maintaining these aspects. Traditional security measures are often inadequate due to the absence of a fixed infrastructure, high mobility, and the heterogeneous environment in VANETs [21].
Vehicular ad hoc networks (VANETs) are highly susceptible to various forms of attacks [22], including denial-of-service, impersonation, and the spread of false information, among others [23][24]. Traditional security mechanisms often fall short with respect to adequately securing these networks due to their unique characteristics such as high mobility and varying node densities. Public key infrastructure (PKI) has been widely used but comes with limitations when dealing with high-speed, short-range vehicular interactions [25][26].
Traditional PKI systems are predicated on the assumption of relatively stable and prolonged interactions between entities. However, VANETs are characterized by high-speed movement and fleeting encounters between vehicles. This dynamic nature can lead to several issues with PKI, such as the following:
  • Rapid Change of Context: The fast-paced environment can outpace the PKI’s ability to update and validate certificates, thereby leading to delays or errors in authentication.
  • Scalability Concerns: The sheer volume of high-frequency interactions requires a PKI system to handle a significant number of certificate validations within a minimal time frame, which can form a scalability bottleneck.
  • Latency in Certificate Revocation: The time-sensitive nature of revoking compromised certificates can be at odds with the quick interaction times, thereby potentially allowing unauthorized access.
Blockchain technology has recently shown promise in enhancing VANET security by providing a decentralized approach that could potentially solve many of the challenges associated with traditional architectures [27][28]:
  • Decentralization: The blockchain operates on a peer-to-peer network that inherently supports the dynamic and decentralized nature of VANETs, thereby facilitating faster and more efficient verifications.
  • Immediate Validation: Transactions and communications in a blockchain network can be validated in real time, which aligns well with the high-speed requirements of VANETs.
  • Immutable Ledger: The blockchain ledger [29] provides a tamper-proof record of all transactions, including authentications and data exchanges, thereby enhancing trust in vehicular communications.
Various studies have investigated the application of blockchain technology in managing secure and reliable data exchanges in VANETs. In the following Figure 1, a general view of the blockchain-based architectures in VANETs is presented. As can be seen, while input communications in blockchain networks require a specific cryptographic configuration and service interface (only deployed in the RSU), output validated data are published as public events (output flows in the blockchain networks can only be managed as events), and the vehicle node can capture that information without the intervention of the RSU.
Figure 1. Blockchain-based architecture for VANETs.
On the other hand, the evolving field of trust computation offers several approaches for improving VANET security [30]. Methods for calculating trust [31][32] can be broadly divided into categories based on multiweight fusion [33][34], Bayesian inference (BI) [21][35][36], Dempster–Shafer (D-S) theory [37], fuzzy logic [38][39], and three-valued subjective logic (3VSL) [40][41]. Bayesian inference has shown to be particularly suitable for the quantitative judgement of interactive trust in the VANET context [42][43][44][45].
Other authors have emphasized the pressing concern of cyber attacks on data stored in cloud servers [46]. Or, they have pointed out the vulnerability of VANETs to these attacks due to the critical and sensitive nature of the data they handle [47]. A decentralized approach using blockchain technology was proposed to safeguard this data [48]. By employing cryptographic techniques, the information was encrypted, thus bolstering its confidentiality and anonymity [49]. However, limitations were also observed, mainly regarding scalability and the high computational power required for these cryptographic processes [50].
The focus shifted towards the centralization of data management in VANETs, which traditionally relies on systems maintained by vehicle service providers [51][52]. The risks associated with such a setup were recognized, including system failures and protection disagreements [53][54]. To address these concerns, a blockchain-based architectural design was proposed that employs sovereign identity for enhancing the security of data and uses a multitier, capability-based authentication process [55][56]. Although promising, the research also highlighted the need for robust standardization to ensure the seamless integration and interoperability of the proposed system [57].
In response to the exponential rise in wireless connected devices [58], the limitations of cloud computing in effectively addressing associated security concerns were pointed out [59]. A blockchain-based structure was proposed that was specifically designed for VANETs, thus focusing on resolving performance and scalability issues [48]. The results showed an improvement in data management and security. However, concerns about the implementation complexities of integrating blockchain technology into existing VANET systems were also raised [6].
The primary feature of the blockchain that benefits VANETs is its decentralized nature, which eliminates the need for a central authority, thereby reducing the risk of single-point failures and potential bottlenecks in data flow. Additionally, the transparency and immutability of blockchain technology ensure the integrity of the data, thereby making it resistant to tampering and forgery [21].
Various security issues like forgery, denial-of-service, and smart card theft threats that plague VANETs were tackled [37]. A blockchain-enabled authentication and authorization system for VANETs was presented, which efficiently managed privacy and information integrity [60]. Despite the contributions, the need for further optimization to improve the system’s efficiency was acknowledged, especially under high network load conditions.
Finally, it was explored how VANETs rely on a third-party financial intermediary to share information electronically [61]. A paradigm shift towards blockchain was argued for, thereby eliminating the need for a central authority and fostering a more transparent and trusting environment [27]. A blockchain-enabled platform was developed to facilitate information exchange between domains [60]. However, the necessity of efficient consensus algorithms to manage the increased network traffic effectively was also highlighted [62]. Nervetherless, the combination of VANETs and blockchain technology has great potential to address the various security challenges faced by VANETs [63].

3. Advantages and Benefits of the Proposed Technology

The inherently decentralized architecture of the blockchain facilitates accurate data verification and traceability without reliance on central authoritative entities, thereby significantly mitigating vulnerabilities to a wide array of cybersecurity threats [19]. The ledger’s immutability guarantees the permanence of each recorded transaction or vehicular event, thus assuring data integrity and enabling reliable audit processes and crossverification by authenticated network participants [15].
The blockchain’s integration within VANETs not only fortifies the security framework, but also introduces an efficient paradigm for managing vehicular location data [20]. Each entity, whether a vehicular node or a roadside unit, becomes an integral component of the blockchain consensus mechanism, thereby ensuring the authenticity and timeliness of shared data [11]. Smart contracts autonomously execute on the blockchain, thus streamlining the validation process for location and movement data. This automation circumvents the need for manual verification, thereby enhancing the functional efficiency of intelligent transportation systems [9]. Moreover, the principles of immutability and transparency that are foundational to the blockchain provide a trustworthy platform for exchanging critical security data [64][65], such as traffic alerts and vehicle status updates [10].
By leveraging the intrinsic features of the blockchain (its decentralization, transparency, and immutability) we facilitate a paradigm shift regarding how vehicular data is authenticated and managed. This shift not only augments system reliability, but also elevates data verifiability to unprecedented levels. Through the blockchain-enabled framework, each vehicle becomes a node within a vast, interconnected network, thereby contributing to and benefitting from a collective pool of shared positional and movement data. The consensus algorithms intrinsic to blockchain technology ensure that only verified and authenticated data are appended to the ledger. This process effectively neutralizes the risks of tampered or falsified data, which could otherwise lead to catastrophic outcomes in real-time vehicular navigation and coordination [12].
Moreover, the implementation of smart contracts automates the enforcement of predefined rules and policies, which govern the data sharing and validation processes. These smart contracts, once deployed, act without the need for centralized oversight, thus ensuring that vehicles operate within the agreed-upon guidelines and maintaining the integrity and reliability of the vehicular network.
The blockchain’s ledger provides a permanent, tamper-proof record of all vehicular activities, thereby creating a reliable source of data for analytics and decision-making processes. It also serves as an immutable point of reference for auditing and legal purposes, thereby enhancing accountability within the network. As such, the integration of blockchain technology into VANETs presents a robust solution to the challenges of vehicle tracking, positioning, and movement, thereby establishing a new standard for security and efficiency in intelligent transportation systems [12].

References

  1. Menouar, H.; Guvenc, I.; Akkaya, K.; Uluagac, A.S.; Kadri, A.; Tuncer, A. UAV-enabled intelligent transportation systems for the smart city: Applications and challenges. IEEE Commun. Mag. 2017, 55, 22–28.
  2. Asra, S.A. Security Issues of Vehicular Ad Hoc Networks (VANET): A Systematic Review. TIERS Inf. Technol. J. 2022, 3, 17–27.
  3. Afzal, Z.; Kumar, M. Security of vehicular ad-hoc networks (VANET): A survey. J. Phys. Conf. Ser. 2020, 1427, 012015.
  4. Sweeney, L. k-anonymity: A model for protecting privacy. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 2002, 10, 557–570.
  5. Atzori, L.; Iera, A.; Morabito, G. The internet of things: A survey. Comput. Netw. 2010, 54, 2787–2805.
  6. Li, R.; Song, T.; Mei, B.; Li, H.; Cheng, X.; Sun, L. Blockchain for large-scale internet of things data storage and protection. IEEE Trans. Serv. Comput. 2018, 12, 762–771.
  7. Wang, L.; Zheng, D.; Guo, R.; Hu, C.; Jing, C. A blockchain-based privacy-preserving authentication scheme with anonymous identity in vehicular networks. Int. J. Netw. Secur. 2020, 22, 981–990.
  8. Wang, X.; Xu, C.; Zhou, Z.; Yang, S.; Sun, L. A survey of blockchain-based cybersecurity for vehicular networks. In Proceedings of the 2020 International Wireless Communications and Mobile Computing (IWCMC), Limassol, Cyprus, 15–19 June 2020; pp. 740–745.
  9. Diallo, E.H.; Dib, O.; Al Agha, K. A scalable blockchain-based scheme for traffic-related data sharing in VANETs. Blockchain Res. Appl. 2022, 3, 100087.
  10. Mollah, M.B.; Zhao, J.; Niyato, D.; Guan, Y.L.; Yuen, C.; Sun, S.; Lam, K.-Y.; Koh, L.H. Blockchain for the internet of vehicles towards intelligent transportation systems: A survey. IEEE Internet Things J. 2020, 8, 4157–4185.
  11. Mikavica, B.; Kostić-Ljubisavljević, A. Blockchain-based solutions for security, privacy, and trust management in vehicular networks: A survey. J. Supercomput. 2021, 77, 9520–9575.
  12. Javaid, U.; Aman, M.N.; Sikdar, B. DrivMan: Driving trust management and data sharing in VANETS with blockchain and smart contracts. In Proceedings of the 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), Kuala Lumpur, Malaysia, 28 April–1 May 2019; pp. 1–5.
  13. Yeh, L.Y.; Shen, N.X.; Hwang, R.H. Blockchain-based privacy-preserving and sustainable data query service over 5g-vanets. IEEE Trans. Intell. Transp. Syst. 2022, 23, 15909–15921.
  14. Guehguih, B.; Lu, H. Blockchain-based privacy-preserving authentication and message dissemination scheme for vanet. In Proceedings of the 2019 5th International Conference on Systems, Control and Communications, Wuhan, China, 21–23 December 2019; pp. 16–21.
  15. Kouicem, D.E.; Bouabdallah, A.; Lakhlef, H. An efficient and anonymous blockchain-based data sharing scheme for vehicular networks. In Proceedings of the 2020 IEEE Symposium on Computers and Communications (ISCC), Rennes, France, 7–10 July 2020; pp. 1–6.
  16. Guo, Z.; Wang, G.; Li, Y.; Ni, J.; Du, R.; Wang, M. Accountable Attribute-Based Data-Sharing Scheme Based on Blockchain for Vehicular Ad Hoc Network. IEEE Internet Things J. 2022, 10, 7011–7026.
  17. Tan, H.; Chung, I. Secure authentication and key management with blockchain in VANETs. IEEE Access 2019, 8, 2482–2498.
  18. Xie, L.; Ding, Y.; Yang, H.; Wang, X. Blockchain-based secure and trustworthy Internet of Things in SDN-enabled 5G-VANETs. IEEE Access 2019, 7, 56656–56666.
  19. Joshi, G.P.; Perumal, E.; Shankar, K.; Tariq, U.; Ahmad, T.; Ibrahim, A. Toward blockchain-enabled privacy-preserving data transmission in cluster-based vehicular networks. Electronics 2020, 9, 1358.
  20. Li, B.; Liang, R.; Zhu, D.; Chen, W.; Lin, Q. Blockchain-based trust management model for location privacy preserving in VANET. IEEE Trans. Intell. Transp. Syst. 2020, 22, 3765–3775.
  21. Zhang, J.; Zheng, K.; Zhang, D.; Yan, B. AATMS: An anti-attack trust management scheme in VANET. IEEE Access 2020, 8, 21077–21090.
  22. Eziama, E.; Tepe, K.; Balador, A.; Nwizege, K.S.; Jaimes, L.M. Malicious node detection in vehicular ad-hoc network using machine learning and deep learning. In Proceedings of the 2018 IEEE Globecom Workshops (GC Wkshps), Abu Dhabi, United Arab Emirates, 9–13 December 2018; pp. 1–6.
  23. Sheikh, M.S.; Liang, J.; Wang, W. A survey of security services, attacks, and applications for vehicular ad hoc networks (vanets). Sensors 2019, 19, 3589.
  24. Sedar, R.; Kalalas, C.; Vázquez-Gallego, F.; Alonso, L.; Alonso-Zarate, J. A comprehensive survey of v2x cybersecurity mechanisms and future research paths. IEEE Open J. Commun. Soc. 2023, 4, 325–391.
  25. Yu, R.; Kang, J.; Huang, X.; Xie, S.; Zhang, Y.; Gjessing, S. MixGroup: Accumulative pseudonym exchanging for location privacy enhancement in vehicular social networks. IEEE Trans. Dependable Secur. Comput. 2015, 13, 93–105.
  26. Lo, N.W.; Tsai, J.L. An efficient conditional privacy-preserving authentication scheme for vehicular sensor networks without pairings. IEEE Trans. Intell. Transp. Syst. 2015, 17, 1319–1328.
  27. Nakamoto, S. Bitcoin: A Peer-to-Peer Electronic Cash System. 2008. Available online: https://bitcoin.org/bitcoin.pdf (accessed on 1 October 2023).
  28. Zou, S.; Xi, J.; Wang, S.; Lu, Y.; Xu, G. Reportcoin: A novel blockchain-based incentive anonymous reporting system. IEEE Access 2019, 7, 65544–65559.
  29. Yuan, Y.; Wang, F.Y. Towards blockchain-based intelligent transportation systems. In Proceedings of the 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil, 1–4 November 2016; pp. 2663–2668.
  30. Li, W.; Song, H. ART: An attack-resistant trust management scheme for securing vehicular ad hoc networks. IEEE Trans. Intell. Transp. Syst. 2015, 17, 960–969.
  31. Ahmad, F.; Kurugollu, F.; Kerrache, C.A.; Sezer, S.; Liu, L. Notrino: A novel hybrid trust management scheme for internet-of-vehicles. IEEE Trans. Veh. Technol. 2021, 70, 9244–9257.
  32. Oubabas, S.; Aoudjit, R.; Rodrigues, J.J.; Talbi, S. Secure and stable vehicular ad hoc network clustering algorithm based on hybrid mobility similarities and trust management scheme. Veh. Commun. 2018, 13, 128–138.
  33. Yang, Q.; Wang, H. Toward trustworthy vehicular social networks. IEEE Commun. Mag. 2015, 53, 42–47.
  34. Siddiqui, S.A.; Mahmood, A.; Zhang, W.E.; Sheng, Q.Z. Machine learning based trust model for misbehaviour detection in internet-of-vehicles. In Proceedings of the Neural Information Processing: 26th International Conference, ICONIP 2019, Sydney, NSW, Australia, 12–15 December 2019; pp. 512–520.
  35. Fang, W.; Zhang, W.; Liu, Y.; Yang, W.; Gao, Z. BTDS: Bayesian-based trust decision scheme for intelligent connected vehicles in VANETs. Trans. Emerg. Telecommun. Technol. 2020, 31, e3879.
  36. Halabi, T.; Zulkernine, M. Trust-based cooperative game model for secure collaboration in the internet of vehicles. In Proceedings of the ICC 2019–2019 IEEE International Conference on Communications (ICC), Shanghai, China, 20–24 May 2019; pp. 1–6.
  37. Raya, M.; Papadimitratos, P.; Gligor, V.D.; Hubaux, J.P. On data-centric trust establishment in ephemeral ad hoc networks. In Proceedings of the IEEE INFOCOM 2008-The 27th Conference on Computer Communications, Phoenix, AZ, USA, 13–18 April 2008; pp. 1238–1246.
  38. Mármol, F.G.; Pérez, G.M. TRIP, a trust and reputation infrastructure-based proposal for vehicular ad hoc networks. J. Netw. Comput. Appl. 2012, 35, 934–941.
  39. Guleng, S.; Wu, C.; Chen, X.; Wang, X.; Yoshinaga, T.; Ji, Y. Decentralized trust evaluation in vehicular Internet of Things. IEEE Access 2019, 7, 15980–15988.
  40. Xu, S.; Guo, C.; Hu, R.Q.; Qian, Y. Blockchain-inspired secure computation offloading in a vehicular cloud network. IEEE Internet Things J. 2021, 9, 14723–14740.
  41. Zhang, H.; Bian, X.; Xu, Y.; Xiang, S.; He, X. Blockchain-assisted vehicle reputation management method for VANET. J. Xidian Univ. 2022, 49, 49–59.
  42. Fei, Z.; Liu, K.; Huang, B.; Zheng, Y.; Xiang, X. Dirichlet process mixture model based nonparametric bayesian modeling and variational inference. In Proceedings of the 2019 Chinese Automation Congress (CAC), Hangzhou, China, 22–24 November 2019; pp. 3048–3051.
  43. Gurung, S.; Lin, D.; Squicciarini, A.; Bertino, E. Information-oriented trustworthiness evaluation in vehicular ad-hoc networks. In Proceedings of the Network and System Security: 7th International Conference, NSS 2013, Madrid, Spain, 3–4 June 2013; Springer: Berlin/Heidelberg, Germany; pp. 94–108.
  44. Sugumar, R.; Rengarajan, A.; Jayakumar, C. Trust based authentication technique for cluster based vehicular ad hoc networks (VANET). Wirel. Netw. 2018, 24, 373–382.
  45. Dahmane, S.; Kerrache, C.A.; Lagraa, N.; Lorenz, P. WeiSTARS: A weighted trust-aware relay selection scheme for VANET. In Proceedings of the 2017 IEEE International Conference on Communications (ICC), Paris, France, 21–25 May 2017; pp. 1–6.
  46. Zhou, M.; Zhang, R.; Xie, W.; Qian, W.; Zhou, A. Security and privacy in cloud computing: A survey. In Proceedings of the 2010 Sixth International Conference on Semantics, Knowledge and Grids, Beijing, China, 1–3 November 2010; pp. 105–112.
  47. Golle, P.; Greene, D.; Staddon, J. Detecting and correcting malicious data in VANETs. In Proceedings of the 1st ACM International Workshop on Vehicular Ad Hoc Networks, Philadelphia, PA, USA, 1 October 2004; pp. 29–37.
  48. Mistry, I.; Tanwar, S.; Tyagi, S.; Kumar, N. Blockchain for 5G-enabled IoT for industrial automation: A systematic review, solutions, and challenges. Mech. Syst. Signal Process. 2020, 135, 106382.
  49. Diffie, W.; Hellman, M.E. New directions in cryptography. In Democratizing Cryptography: The Work of Whitfield Diffie and Martin Hellman; Association for Computing Machinery: New York, NY, USA, 2022; pp. 365–390.
  50. Narayanan, A.; Bonneau, J.; Felten, E.; Miller, A.; Goldfeder, S. Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction; Princeton University Press: Princeton, NJ, USA, 2016.
  51. Ma, Z.; Zhang, J.; Guo, Y.; Liu, Y.; Liu, X.; He, W. An efficient decentralized key management mechanism for VANET with blockchain. IEEE Trans. Veh. Technol. 2020, 69, 5836–5849.
  52. Feng, J.; Wang, Y.; Wang, J.; Ren, F. Blockchain-based data management and edge-assisted trusted cloaking area construction for location privacy protection in vehicular networks. IEEE Internet Things J. 2020, 8, 2087–2101.
  53. Zhu, X.; Jiang, S.; Wang, L.; Li, H. Efficient privacy-preserving authentication for vehicular ad hoc networks. IEEE Trans. Veh. Technol. 2013, 63, 907–919.
  54. Su, J.; Ren, R.; Li, Y.; Lau, R.Y.; Shi, Y. Trusted blockchain-based signcryption protocol and data management for authentication and authorization in VANETs. Wirel. Commun. Mob. Comput. 2022, 2022, 9572992.
  55. Grover, J. Security of Vehicular Ad Hoc Networks using blockchain: A comprehensive review. Veh. Commun. 2022, 34, 100458.
  56. Zhang, X.; Li, R.; Cui, B. A security architecture of VANET based on blockchain and mobile edge computing. In Proceedings of the 2018 1st IEEE International Conference on Hot Information-Centric Networking (HotICN), Shenzhen, China, 15–17 August 2018; pp. 258–259.
  57. Disterer, G. ISO/IEC 27000, 27001 and 27002 for information security management. J. Inf. Secur. 2013, 4, 92–100.
  58. Ashton, K. That ‘internet of things’ thing. RFID J. 2009, 22, 97–114.
  59. Fernando, N.; Loke, S.W.; Rahayu, W. Mobile cloud computing: A survey. Future Gener. Comput. Syst. 2013, 29, 84–106.
  60. Dorri, A.; Kanhere, S.S.; Jurdak, R.; Gauravaram, P. Blockchain for IoT security and privacy: The case study of a smart home. In Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, HI, USA, 13–17 March 2017; pp. 618–623.
  61. Kshetri, N. Can blockchain strengthen the internet of things? IT Prof. 2017, 19, 68–72.
  62. Bonneau, J.; Miller, A.; Clark, J.; Narayanan, A.; Kroll, J.A.; Felten, E.W. Sok: Research perspectives and challenges for bitcoin and cryptocurrencies. In Proceedings of the 2015 IEEE Symposium on Security and Privacy, San Jose, CA, USA, 17–21 May 2015; pp. 104–121.
  63. Li, Z.; Kang, J.; Yu, R.; Ye, D.; Deng, Q.; Zhang, Y. Consortium blockchain for secure energy trading in industrial internet of things. IEEE Trans. Ind. Inform. 2017, 14, 3690–3700.
  64. Wang, Y.; Su, Z.; Zhang, K.; Benslimane, A. Challenges and solutions in autonomous driving: A blockchain approach. IEEE Netw. 2020, 34, 218–226.
  65. Yang, Z.; Zheng, K.; Yang, K.; Leung, V.C. A blockchain-based reputation system for data credibility assessment in vehicular networks. In Proceedings of the 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Montreal, QC, Canada, 8–13 October 2017; pp. 1–5.
More
Information
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : ,
View Times: 257
Revisions: 2 times (View History)
Update Date: 08 Dec 2023
1000/1000
Video Production Service