Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs

Ullah, Ikram; Shah, Munam Ali; Khan, Abid; Maple, Carsten; Waheed, Abdul

doi:10.3390/s21093077

Cited by 10 publications

(11 citation statements)

References 52 publications

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“…As a result, the adversaries can perform background knowledge attack using static pseudonyms to find the RIDs of the users. Some authors propose pseudonym update mechanisms to overcome this issue [17]. On the other hand, internal attackers can distribute misleading information in the networks without being detected because the networks lack tracking methods.…”

Section: Related Workmentioning

confidence: 99%

Secure Message Handling in Vehicular Energy Networks Using Blockchain and Artificially Intelligent IPFS

et al. 2022

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In the underlying work, the problems faced during message dissemination in the conventional Vehicular Energy Networks (VENs) like lack of security, breach of personal identities, absence of trust between vehicle owners, etc., are tackled. In this study, a Blockchain (BC) based announcement system is proposed for VENs to ensure secure and reliable announcement dissemination in the proposed network. The proposed system is a three-layered system comprising message dissemination layer, storage layer and BC layer. In the first layer, all the vehicles are registered through a Certificate Authority (CA), which ensures only the legitimate vehicles become part of the proposed network and interact with each other. Later, in the second layer, the data sent by the vehicles is stored at the artificial intelligence based Interplanetary File System (IPFS), which is incorporated with the Road Side Units (RSUs). This ensures reduction in storage cost and data availability. Besides, vehicle owners' privacy is ensured by concealing the real identities of the vehicles. Moreover, the hashes of the data stored in the IPFS are stored in BC in the third layer. Also, lightweight trustworthiness verification of the vehicles, reputation based incentivization and concealing predictable trends in vehicles' reputation scores are performed in the same layer. Overall, the novelty of the proposed work lies in the fact that the proposed system efficiently tackles different problems encountered in the existing systems simultaneously. Through extensive simulations, it is inferred that the computational time is reduced by 15-18% and the storage overhead is reduced by 80-85%, respectively when storing hash of data on the BC network as compared to storing actual data on the network.

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Section: Related Workmentioning

confidence: 99%

Secure Message Handling in Vehicular Energy Networks Using Blockchain and Artificially Intelligent IPFS

et al. 2022

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“…The signature of a large group is difficult to manage, while smaller groups affect the privacy protection level [33]. In [38], a dynamic grouping and virtual pseudonym exchange scheme is proposed in which diverse traffic conditions are utilized to update pseudonyms of vehicles for location protection. Some techniques employ dummy data or inaccurate data to generate confusion for an adversary to identify the real location of a vehicle.…”

Section: Related Workmentioning

confidence: 99%

A Distributed Mix-Context-Based Method for Location Privacy in Road Networks

et al. 2021

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Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages in an open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by a vehicle using sensitive information transmitted in beacons such as vehicle identity and location. By matching the vehicle identity used in beacon messages at various locations, an adversary learns the location history of a vehicle. This compromises the privacy of the vehicle driver. In existing research work, pseudonyms are used in place of the actual vehicle identity in the beacons. Pseudonyms should be changed regularly to safeguard the location privacy of vehicles. However, applying simple change in pseudonyms does not always provide location privacy. Existing schemes based on mix zones operate efficiently in higher traffic environments but fail to provide privacy in lower vehicle traffic densities. In this paper, we take the problem of location privacy in diverse vehicle traffic densities. We propose a new Crowd-based Mix Context (CMC) privacy scheme that provides location privacy as well as identity protection in various vehicle traffic densities. The pseudonym changing process utilizes context information of road such as speed, direction and the number of neighbors in transmission range for the anonymisation of vehicles, adaptively updating pseudonyms based on the number of a vehicle neighbors in the vicinity. We conduct formal modeling and specification of the proposed scheme using High-Level Petri Nets (HPLN). Simulation results validate the effectiveness of CMC in terms of location anonymisation, the probability of vehicle traceability, computation time (cost) and effect on vehicular applications.

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“…In ref. [25], the concept of dynamic pseudonym has been used instead of vehicle ID to disguise adversary. A dynamic grouping and virtual pseudonym-changing method are proposed in which, based on status, dynamic groups are created with changing pseudonyms.…”

Section: Related Workmentioning

confidence: 99%

A Privacy Preserved, Trust Relationship (PTR) Model for Internet of Vehicles

et al. 2021

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The Internet of vehicles (IoV) depicts a reality where ordinary things are connected to vehicular ad-hoc networks (VANETs), allowing them to transmit and collaborate. By placing these regular objects in VANETs and making them available at any time, this network and data sharing may raise real privacy and security issues. Thus, group-based communication is mostly preferred in the literature. However, in heavy network scenarios, cluster-based communication mostly leads to additional overload in the form of the group leader that causes delay and disrupts the performance of a network. Due to the interaction of VANETs with applications that are not stable for life, privacy and security mechanism for detecting many malicious nodes is in great demand. Therefore, a multi-phantom node selection has been proposed in this paper to select trustworthy, normal, and malicious nodes. The multi-phantom node scheme is proposed to reduce the phantom node load, where the multi-lateral nodes in a cluster act as a phantom node to share the load. A multi criteria decision-making (MCDM) methodology (analytic network process) is used to optimize the phantom node to pre-serve privacy using the privacy preserved trust relationship (PTR) model. The results show checking the stability of parameters and using sensitivity analysis by considering different scenarios for the most optimal phantom node to preserve vehicle location privacy. The impact of the proposed model will be more clearly visible in its real-time implementation in urban areas vehicle networks.

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Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs

Cited by 10 publications

References 52 publications

Secure Message Handling in Vehicular Energy Networks Using Blockchain and Artificially Intelligent IPFS

Secure Message Handling in Vehicular Energy Networks Using Blockchain and Artificially Intelligent IPFS

A Distributed Mix-Context-Based Method for Location Privacy in Road Networks

A Privacy Preserved, Trust Relationship (PTR) Model for Internet of Vehicles

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