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Ciphertext-Policy Attribute-Based Encryption for Cloud Storage: Toward Data Privacy and Authentication in AI-Enabled IoT System

Author

Listed:
  • P. Chinnasamy

    (Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad 500043, India)

  • P. Deepalakshmi

    (Department of Computer Science and Engineering, Kalasalingam Academy of Research and Education, Srivilliputtur 626128, India)

  • Ashit Kumar Dutta

    (Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Ad Diriyah, Riyadh 13713, Saudi Arabia)

  • Jinsang You

    (Seculayer Company, Ltd., Seoul 04784, Korea)

  • Gyanendra Prasad Joshi

    (Department of Computer Science and Engineering, Sejong University, Seoul 05006, Korea)

Abstract

People can store their data on servers in cloud computing and allow public users to access data via data centers. One of the most difficult tasks is to provide security for the access policy of data, which is also needed to be stored at cloud servers. The access structure (policy) itself may reveal partial information about what the ciphertext contains. To provide security for the access policy of data, a number of encryption schemes are available. Among these, CP-ABE (Ciphertext-Policy Attribute-Based Encryption) scheme is very significant because it helps to protect, broadcast, and control the access of information. The access policy that is sent as plaintext in the existing CP-ABE scheme along with a ciphertext may leak user privacy and data privacy. To resolve this problem, we hereby introduce a new technique, which hides the access policy using a hashing algorithm and provides security against insider attack using a signature verification scheme. The proposed system is compared with existing CP-ABE schemes in terms of computation and expressive policies. In addition, we can test the functioning of any access control that could be implemented in the Internet of Things (IoT). Additionally, security against indistinguishable adaptive chosen ciphertext attacks is also analyzed for the proposed work.

Suggested Citation

  • P. Chinnasamy & P. Deepalakshmi & Ashit Kumar Dutta & Jinsang You & Gyanendra Prasad Joshi, 2021. "Ciphertext-Policy Attribute-Based Encryption for Cloud Storage: Toward Data Privacy and Authentication in AI-Enabled IoT System," Mathematics, MDPI, vol. 10(1), pages 1-24, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2021:i:1:p:68-:d:711413
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    Citations

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    Cited by:

    1. Zizhao Xie & Jingru Sun & Yiping Tang & Xin Tang & Oluyomi Simpson & Yichuang Sun, 2023. "A K-SVD Based Compressive Sensing Method for Visual Chaotic Image Encryption," Mathematics, MDPI, vol. 11(7), pages 1-20, March.
    2. Jialu Hao & Wei Wu & Shuo Wang & Xiaoge Zhong & Guang Chu & Feng Shao, 2022. "A Delegation Attack Method on Attribute-Based Signatures and Probable Solutions," Mathematics, MDPI, vol. 11(1), pages 1-14, December.

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