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Privacy-Preserving Data Outsourcing with Integrity Auditing for Lightweight Devices in Cloud Computing

  • Dengzhi Liu
  • Jian ShenEmail author
  • Yuling Chen
  • Chen Wang
  • Tianqi Zhou
  • Anxi Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11449)

Abstract

The cloud can provide unlimited storage space to users via the Internet. Unlike locally data storing, users will lose the direct control of the data after outsourcing it to the cloud. Moreover, the cloud is an untrusted entity. It is possible that the cloud may try to extract, discard and destroy users’ data due to benefits. Hence, the data security in cloud computing needs to be well guaranteed. In this paper, we propose a privacy-preserving data outsourcing scheme with integrity auditing for lightweight devices in cloud computing. On the one hand, the blind signature is used in the proposed scheme to delegate the generation of users’ data signatures to the TPA. On the other hand, based on the property of the BLS signature, the blinded signatures received from the TPA can be verified by the user and the data integrity stored in the cloud can be audited by the TPA. In addition, the proposed scheme supports batch operation. Security analysis shows that the proposed scheme achieves the properties of correctness, privacy-preserving and non-forgeability. Performance analysis indicates that the proposed scheme can be performed with high efficiency.

Keywords

Cloud computing Data outsourcing Integrity auditing Batch operation 

Notes

Acknowledgments

This work is supported by the National Natural Science Foundation of China under Grant No. U1836115, No. 61672295, and No. 61672290, the Natural Science Foundation of Jiangsu Province under Grant No. BK20181408, the Foundation of Guizhou Provincial Key Laboratory of Public Big Data under Grant No. 2018BDKFJJ003, Guangxi Key Laboratory of Cryptography and Information Security under Grant No. GCIS201715, the State Key Laboratory of Information Security under Grant No. 2017-MS-10, the CICAEET fund, and the PAPD fund.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Dengzhi Liu
    • 1
  • Jian Shen
    • 1
    • 2
    Email author
  • Yuling Chen
    • 2
  • Chen Wang
    • 1
  • Tianqi Zhou
    • 1
  • Anxi Wang
    • 1
  1. 1.Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science and TechnologyNanjingChina
  2. 2.Guizhou Provincial Key Laboratory of Public Big DataGuiyangChina

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