EditorialSecurity and Privacy Challenges in Vehicular Cloud Computing

Rongxing Lu,1 Yogachandran Rahulamathavan,2 Hui Zhu,3 Chang Xu,4 and Miao Wang5

1University of New Brunswick, Fredericton, NB, Canada2Loughborough University in London, London, UK3Xidian University, Xi’an, China4Beijing Institute of Technology, Beijing, China5McMaster University, Hamilton, ON, Canada

Correspondence should be addressed to Rongxing Lu; rxlu@ieee.org

Received 24 November 2016; Accepted 24 November 2016

Copyright © 2016 Rongxing Lu et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The recent developments and deployments of connected andautonomous vehicular network or the so-called vehicularad hoc networks (VANETs) offer the promise of significantbenefits to the society and environment including robustroad safety and intelligent traffic management. When aswarm of vehicles with sophisticated sensing and connectiv-ity capabilities travel together, aggregating the resources suchas sensors, sensor results, and onboard computing infras-tructure in vehicles creates a platform equivalent to cloudcomputing. As a special cloud computing platform, Vehic-ular Cloud Computing (VCC), which seamlessly combinescloud computing and VANETs, has been recently proposedto accelerate the adoption of VANETs. VCC is a mobilecomputing paradigm, which consists of in-motion vehiclescooperating with each other to achieve a bunch of practicalapplications, such as collaborative package delivery andinformation dissemination. Essentially, VCC coordinates thecomputing, communication, sensing, and storage resourcesof the vehicles on the road to balance the service requirementsand the hardware limitation. Nevertheless, different from thetraditional cloud infrastructure, VCC requires sophisticatedsecurity and privacy protectionmechanisms as the legitimateusers and attackers have the same privileges in mobile VCC.Therefore, in order to enhance the security and scalabilityof VCC, a number of crucial issues must be addressed suchas trust model, data security, connection fault, and querytracking attacks. In this special issue on security and privacychallenges in VCC, we have invited a few papers that addresssuch issues.

The paper “On Preventing Location Attacks for UrbanVehicular Networks” focuses on preventing potential attacksfrom a perspective of location prediction, which proposesa sophisticated prediction model to predict driver’s nextlocation, analyzes the restriction of the proposed advancedpredication model, and presents a schema to decrease therisks of location prediction attacks. Experimental resultsobtained from the real-world vehicular network data havedemonstrated the effectiveness of preventing location attacksin urban vehicular networks.

The paper “Conditional Ciphertext-Policy Attribute-Based Encryption Scheme in Vehicular Cloud Comput-ing” presents an expressive and fine-grained conditionalciphertext-policy attribute based encryption (C-CP-ABE)scheme in vehicle cloud computing, which can maintainboth data security and system efficiency. Compared withtraditional CP-ABE, the scheme brings a trivial amount ofstorage overhead and a lower amount of computations butcan associate one ciphertext with different access trees underdifferent conditions.

The paper “A Safety Resource Allocation Mechanismagainst Connection Fault for Vehicular Cloud Computing”discusses the vehicle connection fault issue and proposesa safety resource allocation mechanism against connectionfault in VCC by using a modified workflow with predictioncapability. In themechanism, the connection fault probabilitymodel of the moving vehicles is proposed firstly. And thena safety resource allocation algorithm is proposed to realizethe safety resource allocation for VCC. Extensive evaluations

Hindawi Publishing CorporationMobile Information SystemsVolume 2016, Article ID 6812816, 2 pageshttp://dx.doi.org/10.1155/2016/6812816

2 Mobile Information Systems

demonstrate that the proposal can improve both reliabilityand real-time performance of VCC.

The paper “LSOT: A Lightweight Self-Organized TrustModel in VANETs” addresses the trust management inVANETs and proposes a novel lightweight self-organizedtrust model in VANETs. The model combines both trust cer-tificate-based and recommendation-based trust evaluations,and the evaluation in it can be made quickly and reaches anexcellent performance in a lightweight manner.

The paper “A Trust-Based Model for Security Coop-erating in Vehicular Cloud Computing” describes a trust-based model for security cooperating to promote the securecooperation in VCC, in which a double board based trustestimation and correction scheme is proposed to predict thereliability of vehicles and guide the selection of trustworthycooperative vehicles in a more effective manner.

The paper “A Privacy-Preserving Location-Based Systemfor Continuous Spatial Queries” proposes a novel locationcloaking method to resist query tracking attacks. Comparedwith previous location cloaking methods, this proposedmethod can generate minimized cloaked regions while pro-tecting the location and trajectory privacy of the query issuerin VCC.

Rongxing LuYogachandran Rahulamathavan

Hui ZhuChang Xu

Miao Wang

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