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Bioinspired FHE model with recursive revokable selective access control for attribute-based privacy preservation

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Abstract

Access control and authentication are two aspects of cyber-physical systems that improve their usability, security and accessibility. Along with these aspects, data privacy and security are also considered when designing highly efficient and secure data and control sharing models for cloud-based deployments. Existing methods that combine these models are highly complex or do not provide comprehensive security when tested under real-time attack scenarios. Most of these models are also non-reconfigurable, limiting their scalability when used for large-scale deployments. Hence, a novel Bioinspired Fully Homomorphic Encryption Model with Recursive Revokable Selective Access Control for Attribute-Based Privacy Preservation is discussed in this text. The proposed Model initially uses a GWO Model for continuous performance tuning of Fully Homomorphic Encryption (FHE) blocks, which assists in scaling it for different cloud deployments. The GWO Method models a fitness function that considers encryption strength and speed and maximizes them to generate highly secure and optimized FHE configurations. Due to the use of optimized FHE (oFHE), the deployment can share unprocessed data with trusted and non-trusted third parties for processing and visualization purposes. The oFHE Model is cascaded with a recursive and revokable access control model that assists in incorporating fine-grained control over different ownership-based cloud entities. This Model allows users to send ownership requests for multiple entities, which entity owners can actuate on a per-entity basis. Furthermore, requesting users cannot preview entity-level contents without owners’ consent, making the Model highly secure under real-time attack scenarios. The Model also uses header-level checks to mitigate flooding, masquerading, and Sybil attacks, making it secure under internal and attack scenarios. The header-level checking is done based on the user’s previous access patterns, which allows the Model to pre-empt any outlier requests that might be sent by the user and mitigates them based on access pattern types.

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This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Computer Engineering, Ramrao Adik Institute of Technology, D Y Patil Deemed to be University, Nerul, Navi Mumbai, MH, India

    Namrata Jiten Patel

  2. Computer Engineering, SIES Graduate School of Technology, Nerul, Navi Mumbai, MH, India

    Namrata Jiten Patel

  3. Information Technology, Ramrao Adik Institute of Technology, D Y Patil Deemed to be University, Nerul, Navi Mumbai, MH, India

    Ashish Jadhav

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  1. Namrata Jiten Patel
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Correspondence to Namrata Jiten Patel.

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Patel, N.J., Jadhav, A. Bioinspired FHE model with recursive revokable selective access control for attribute-based privacy preservation. Int. j. inf. tecnol. 16, 1769–1781 (2024). https://doi.org/10.1007/s41870-023-01548-5

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