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Identity-Based Public Auditing for Cloud Storage of Internet-of-Vehicles Data
Author(s) -
Hui Tian,
Fang Peng,
Hanyu Quan,
ChinChen Chang
Publication year - 2022
Publication title -
acm transactions on internet technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.667
H-Index - 56
eISSN - 1557-6051
pISSN - 1533-5399
DOI - 10.1145/3433543
Subject(s) - computer science , cloud computing , audit , table (database) , computer security , data sharing , the internet , block (permutation group theory) , cloud storage , scheme (mathematics) , database , world wide web , operating system , medicine , mathematical analysis , alternative medicine , geometry , management , mathematics , pathology , economics
The Internet of Vehicles (IoV), with the help of cloud computing, can provide rich and powerful application services for vehicles and drivers by sharing and analysing various IoV data. However, how to ensure the integrity of IoV data with multiple sources and diversity outsourced in the cloud is still an open challenge. To address this concern, this paper first presents an identity-based public auditing scheme for cloud storage of IoV data, which can fully achieve the essential function and security requirements, such as classified auditing, multi-source auditing and privacy protection. Particularly, we design a new authenticated data structure, called data mapping table, to track the distribution of each type of IoV data to ensure fine and rapid audits. Moreover, our scheme can reduce the overheads for both the key management and the generation of block tags. We formally prove the security of the presented scheme and evaluate its performance by comprehensive comparisons with the state-of-the-art schemes designed for traditional scenarios. The theoretical analyses and experimental results demonstrate that our scheme can securely and efficiently realize public auditing for IoV data, and outperforms the previous ones in both the computation and communication overheads in most cases.

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