Privacy-preserving route reporting scheme for traffic management in VANETs

Rabieh, Khaled; Mahmoud, Mohamed; Younis, Mohamed

doi:10.1109/icc.2015.7249490

Cited by 23 publications

(10 citation statements)

References 14 publications

(16 reference statements)

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“…The use of personal data and the stringent pressure placed by governments and agencies on differential privacy preservation has spurred a flurry of research to prevent models from revealing sensitive data from their training instances [ 197 , 221 ]. Within the ITS domain, it is possible to find many areas in which privacy preservation has recently been a subject of intense research: from origin-destination flow estimation [ 222 ] to route planners [ 223 , 224 ], or pattern mining [ 225 ], a glance at recent literature reveals the momentum this topic has acquired lately. In any of these examples data are available as a result of the sensing pervasiveness (specially in the case of VANETs) and the capture of user data.…”

Section: Emerging Ai Areas Towards Actionable Itsmentioning

confidence: 99%

From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability

Laña

Medina

Vlahogianni

et al. 2021

Sensors

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Advances in Data Science permeate every field of Transportation Science and Engineering, resulting in developments in the transportation sector that are data-driven. Nowadays, Intelligent Transportation Systems (ITS) could be arguably approached as a “story” intensively producing and consuming large amounts of data. A diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers’ personal devices act as sources of data flows that are eventually fed into software running on automatic devices, actuators or control systems producing, in turn, complex information flows among users, traffic managers, data analysts, traffic modeling scientists, etc. These information flows provide enormous opportunities to improve model development and decision-making. This work aims to describe how data, coming from diverse ITS sources, can be used to learn and adapt data-driven models for efficiently operating ITS assets, systems and processes; in other words, for data-based models to fully become actionable. Grounded in this described data modeling pipeline for ITS, we define the characteristics, engineering requisites and challenges intrinsic to its three compounding stages, namely, data fusion, adaptive learning and model evaluation. We deliberately generalize model learning to be adaptive, since, in the core of our paper is the firm conviction that most learners will have to adapt to the ever-changing phenomenon scenario underlying the majority of ITS applications. Finally, we provide a prospect of current research lines within Data Science that can bring notable advances to data-based ITS modeling, which will eventually bridge the gap towards the practicality and actionability of such models.

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Section: Emerging Ai Areas Towards Actionable Itsmentioning

confidence: 99%

From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability

Laña

Medina

Vlahogianni

et al. 2021

Sensors

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“…In order to protect the privacy of vehicles, Rabieh et al [143] proposed a secure routing report mechanism in VANETs. As shown in the network model ( Figure 5) of this mechanism, there are four entities: vehicles, road-side units, the traffic management center and department of motor vehicles.…”

Section: Paillier Algorithmmentioning

confidence: 99%

A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks

Sun

Zhang

et al. 2020

Sensors

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In vehicular ad hoc networks (VANETs), the security and privacy of vehicle data are core issues. In order to analyze vehicle data, they need to be computed. Encryption is a common method to guarantee the security of vehicle data in the process of data dissemination and computation. However, encrypted vehicle data cannot be analyzed easily and flexibly. Because homomorphic encryption supports computations of the ciphertext, it can completely solve this problem. In this paper, we provide a comprehensive survey of secure computation based on homomorphic encryption in VANETs. We first describe the related definitions and the current state of homomorphic encryption. Next, we present the framework, communication domains, wireless access technologies and cyber-security issues of VANETs. Then, we describe the state of the art of secure basic operations, data aggregation, data query and other data computation in VANETs. Finally, several challenges and open issues are discussed for future research.

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“…Public key cryptography has been used to secure different networks/applications, e.g., see [25], [26], [27], [28], [29], and we expect that it will play a major role to secure the smart grid. In [30], Khurana et al have discussed the main security issues in SG.…”

Section: Related Workmentioning

confidence: 99%

Scalable Certificate Revocation Schemes for Smart Grid AMI Networks Using Bloom Filters

Rabieh

Mahmoud

Akkaya

et al. 2017

IEEE Trans. Dependable and Secure Comput.

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Given the scalability of the Advanced Metering Infrastructure (AMI) networks, maintenance and access of certificate revocation lists (CRLs) pose new challenges. It is inefficient to create one large CRL for all the smart meters (SMs) or create a customized CRL for each SM since too many CRLs will be required. In order to tackle the scalability of the AMI network, we divide the network into clusters of SMs, but there is a tradeoff between the overhead at the certificate authority (CA) and the overhead at the clusters. We use Bloom filters to reduce the size of the CRLs in order to alleviate this tradeoff by increasing the clusters' size with acceptable overhead. However, since Bloom filters suffer from false positives, there is a need to handle this problem so that SMs will not discard important messages due to falsely identifying the certificate of a sender as invalid. To this end, we propose two certificate revocation schemes that can identify and nullify the false positives. While the first scheme requires contacting the gateway to resolve them, the second scheme requires the CA additionally distribute the list of certificates that trigger false positives. Using mathematical models, we have demonstrated that the probability of contacting the gateway in the first scheme and the overhead of the second scheme can be very low by properly designing the Bloom filters. In order to assess the scalability and validate the mathematical formulas, we have implemented the proposed schemes using Visual C. The results indicate that our schemes are much more scalable than the conventional CRL and the mathematical and simulation results are almost identical. Moreover, we simulated the distribution of the CRLs in a wireless mesh-based AMI network using ns-3 network simulator and assessed its distribution overhead.

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Privacy-preserving route reporting scheme for traffic management in VANETs

Cited by 23 publications

References 14 publications

From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability

From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability

A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks

Scalable Certificate Revocation Schemes for Smart Grid AMI Networks Using Bloom Filters

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