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Comments on Yu et al’s Shared Data Integrity Verification Protocol

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Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 682))

Abstract

Recently, Yu et al. proposed a secure shared data integrity verification protocol called SDVIP\(^2\) to ensure the integrity of outsourced file in the cloud. Unfortunately, we exploit the vulnerability of their protocol in this paper. We demonstrate an active adversary can modify the outsourced file such that the auditor is unable to detect in the auditing process. At the end of this paper, we also provide two suggestions to fix the proposed attack.

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References

  1. Boneh, D., Franklin, M.: Identity-based encryption from the Weil pairing. In: Proceedings of the 21st Annual International Cryptology Conference on Advances in Cryptology, pp. 213–229. Springer, Heidelberg (2001)

    Google Scholar 

  2. Kim, D., Kwon, H., Hahn, C., Hur, J.: Privacy-preserving public auditing for educational multimedia data in cloud computing. Multimedia Tools Appl. 75(21), 13077–13091 (2016)

    Article  Google Scholar 

  3. Li, C.T., Wu, T.Y., Chen, C.L., Lee, C.C., Chen, C.M.: An efficient user authentication and user anonymity scheme with provably security for IoT-based medical care system. Sensors 17(7), 1482 (2017)

    Article  Google Scholar 

  4. Ni, J., Yu, Y., Mu, Y., Xia, Q.: On the security of an efficient dynamic auditing protocol in cloud storage. IEEE Trans. Parallel Distrib. Syst. 25(10), 2760–2761 (2014)

    Article  Google Scholar 

  5. Wan, C., Zhang, J., Pei, B., Chen, C.: Efficient privacy-preserving third-party auditing for ambient intelligence systems. J. Ambient Intell. Humaniz. Comput. 7(1), 21–27 (2016)

    Article  Google Scholar 

  6. Wang, B., Li, B., Li, H.: Oruta: privacy-preserving public auditing for shared data in the cloud. IEEE Trans. Cloud Comput. 2(1), 43–56 (2014)

    Article  Google Scholar 

  7. Wang, B., Li, H., Li, M.: Privacy-preserving public auditing for shared cloud data supporting group dynamics. In: 2013 IEEE International Conference on Communications (ICC), pp. 1946–1950. IEEE (2013)

    Google Scholar 

  8. Wang, C., Chow, S.S., Wang, Q., Ren, K., Lou, W.: Privacy-preserving public auditing for secure cloud storage. IEEE Trans. Comput. 62(2), 362–375 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  9. Xu, Y., Zhong, H., Cui, J.: An improved identity-based multi-proxy multi-signature scheme. J. Inf. Hiding Multimedia Sig. Process. 7(2), 343–351 (2016)

    Google Scholar 

  10. Yang, K., Jia, X.: An efficient and secure dynamic auditing protocol for data storage in cloud computing. IEEE Trans. Parallel Distrib. Syst. 24(9), 1717–1726 (2013)

    Article  Google Scholar 

  11. Yin, S.L., Li, H., Liu, J.: A new provable secure certificateless aggregate signcryption scheme. J. Inf. Hiding Multimedia Sig. Process. 7(6), 1274–1281 (2016)

    Google Scholar 

  12. Yu, Y., Ni, J., Xia, Q., Wang, X., Yang, H., Zhang, X.: SDIVIP\(^2\): shared data integrity verification with identity privacy preserving in mobile clouds. Pract. Exp. Concurr. Comput. 28(10), 2877–2888 (2016)

    Article  Google Scholar 

  13. Zhang, J., Zhao, X.: Efficient chameleon hashing-based privacy-preserving auditing in cloud storage. Cluster Comput. 19(1), 47–56 (2016)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

The authors would thank anonymous referees for a valuable comments and suggestions. The work of Chien-Ming Chen was supported in part by the Project NSFC (National Natural Science Foundation of China) under Grant number 61402135 and in part by Shenzhen Technical Project under Grant number JCYJ20170307151750788.

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Authors and Affiliations

  1. Fujian Provincial Key Lab of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, 350118, China

    Tsu-Yang Wu & Jeng-Shyang Pan

  2. National Demonstration Center for Experimental Electronic Information and Electrical Technology Education, Fujian University of Technology, Fuzhou, 350118, China

    Tsu-Yang Wu & Jeng-Shyang Pan

  3. School of Computer Science and Technology, Harbin Institute of Technology - Shenzhen, Shenzhen, 518055, China

    Yueshan Lin & Chien-Ming Chen

  4. Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

    King-Hang Wang

Authors
  1. Tsu-Yang Wu
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  2. Yueshan Lin
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  3. King-Hang Wang
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  4. Chien-Ming Chen
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  5. Jeng-Shyang Pan
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Corresponding author

Correspondence to Tsu-Yang Wu .

Editor information

Editors and Affiliations

  1. Department of Computer Science, VŠB-Technical University of Ostrava , Ostrava-Poruba, Czech Republic

    Pavel Krömer

  2. Dept. Lenguajes y Ciencias de la Computación, University of Málaga, Málaga, Spain

    Enrique Alba

  3. Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  4. Department of Computer Science, VŠB-Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Václav Snášel

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Wu, TY., Lin, Y., Wang, KH., Chen, CM., Pan, JS. (2018). Comments on Yu et al’s Shared Data Integrity Verification Protocol. In: Krömer, P., Alba, E., Pan, JS., Snášel, V. (eds) Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2017. Advances in Intelligent Systems and Computing, vol 682. Springer, Cham. https://doi.org/10.1007/978-3-319-68527-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-68527-4_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68526-7

  • Online ISBN: 978-3-319-68527-4

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