PIaaS: Cloud-oriented secure and privacy-conscious parking information as a service using VANETs

摘要

In this paper, we present a VANET-oriented cloud framework more explicitly as VANET commissioning clouds and propose a novel security and privacy-conscious service termed as Parking Information as a Service (PIaaS) employing VANET-oriented clouds. PIaaS offers more elegant parking information from cloud infrastructure to vehicular nodes in a security and privacy-conscious manner. The authentic vehicular nodes (verified by the Traffic Management Bureau (TMB)) along with Parking Side Units (PSUs) communicate their frequent parking information termed as Parking Mobility Vectors (PMVs) with the cloud infrastructure through the Road Side Units (RSUs) named as Communication Terminals (CTs). The CTs forward the inelegant parking information (PMVs) from vehicular nodes to the cloud system, while after processed by the cloud infrastructure in coordination with PSUs construct and transmit more elegant parking information towards the respective physical location of the vehicular nodes. All the communication and exchange of parking information between cloud infrastructure and vehicular nodes is handled in a privacy-conscious anonymous way. It is hard to linkage PMVs to certain vehicular nodes for some kind of information leakage or exploitation. The proposed PIaaS scheme using identity-less PMVs that protects movement profiles of the vehicular nodes from the exploitation of both insider and outsider attacks. Moreover, we proposed a novel geo-location-based parking lock encryption mechanism for location privacy and non-frameability. The cooperation among vehicular nodes, PSUs, and the cloud infrastructure is not only limited to the parking information dissemination but it also provides various kind of useful services such as route-based traffic congestion reports, vehicle theft control, and malicious vehicle detection. The cloud-oriented centralized information storage of the PMVs is very much helpful for analysis and forensics by TMB. In a nutshell, cloud infrastructure process the Big Parking Data (BPD) and yields the most significant parking information in a dynamic, pertinent, privacy and confidentiality preserved manner. (C) 2017 Elsevier B.V. All rights reserved.