Paper Info
Title
Secure and Privacy-Preserving Report De-duplication in the Fog-Based Vehicular Crowdsensing System.
Abstract
Nowadays, vehicles are powerful enough to carry communications, computing and storage capabilities. By interacting with each other and with local (i.e., fog) infrastructures like road-side units, a cohort of vehicles and fog devices could collaboratively provide services like crowdsensing in an unprecedentedly secure and efficient way. However, it has been widely recognized as a challenging work in the vehicular system to develop a secure and efficient sensing task allocation and data de-duplication mechanism. In this paper, we attempt to develop a scheme to address this challenge. Specifically, we use the Elliptic Curves Cryptography (ECC) algorithm to realize secure allocation of location-dependent tasks. During the report submission phase, we adopt the improved message-lock encryption to realize privacy-preserving data de-duplication and to resist the duplicate-faking attacks. Besides, we present a novel signature scheme that can efficiently record the contributions of each vehicle. The security analysis and performance evaluation demonstrate that the proposed scheme can achieve secure and privacy-preserving report de-duplication with moderate computation and communication overhead.
Year
DOI
Venue
2018
10.1109/GLOCOM.2018.8647901
IEEE Global Communications Conference
Field
DocType
ISSN
Data deduplication,Crowdsensing,Cryptography,Computer science,Computer network,Encryption,Security analysis,Computation
Conference
2334-0983
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Shunrong Jiang1474.35
Jianqing Liu24013.39
Mengjie Duan311.03
Liang Min Wang44814.76
Yuguang Fang56982476.76