Lightweight privacy protection scheme for cloud audit
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Author:
Affiliation:

1.Chongqing Communication Design Institute Company Ltd., Chongqing 400041, P. R. China;2.Information Center of Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, P. R. China;3.College of Big Data and Software, Chongqing University, Chongqing 401331, P. R. China

Clc Number:

TP333

Fund Project:

Supported by National Key Research and Development Program of China(2022YFB3402003), Special Key Program for Technological Innovation and Application Development of Chongqing(CSTB2022TIAD-KPX0054) and the Scientific Project of Guizhou Transportation Department(2015121024).

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    Abstract:

    In the context of the explosive growth of big data, the emergence of cloud storage services has significantly facilitated user data storage. The on-demand nature of cloud servers further contributes to their widespread popularity. However, this convenience comes at the expense of direct user control over data stored in the cloud, exposing it to potential damage from various uncertain factors. This brings great challenges to the advancement of cloud storage. To address these challenges, a data auditing scheme is proposed, emphasizing lightweight calculation and verification. This solution streamlines the user’s label calculation operation before uploading data, ensuring data security during the upload process. This approach concurrently reduces the calculation tasks of both the cloud server and the auditor, minimizing overall calculation overhead. To protect user data privacy, the scheme incorporates scrambling encryption inspired by image encryption. This enables users to use random functions to scramble the data block’s location, while still allowing the auditor to calculate the actual data block location for successful auditing. The results show that the proposed solution effectively saves computing resources for users, servers, and auditors during the audit process, thereby improving overall process efficiency.

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张晓琴,姚远,王颖.面向云审计的轻量级隐私保护方案[J].重庆大学学报,2024,47(2):75~83

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History
  • Received:October 13,2022
  • Revised:
  • Adopted:
  • Online: February 20,2024
  • Published:
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