Lightweight multi-copy public data auditing scheme with error localization for fog-assisted digital twins

Pan Yang; Pan Yang

doi:10.3934/bdia.2025006

Big Data and Information Analytics

2025, Volume 9, 106-135. doi: 10.3934/bdia.2025006

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Research article

Lightweight multi-copy public data auditing scheme with error localization for fog-assisted digital twins

Pan Yang ^,

School of Mathematical Sciences, Harbin Engineering University, Harbin 150001, China

Received: 05 September 2025 Revised: 22 October 2025 Accepted: 28 October 2025 Published: 04 November 2025

The integrity and durability of digital twin data determine whether virtual models can meet the requirements of continuous prediction and maintenance of physical entities throughout their lifecycle. Unfortunately, existing cloud data auditing schemes fail to balance achieving lightweight public verification and low communication overhead in multi-cloud and multi-copy scenarios. Additionally, the dual factors of the existence of multiple cloud service providers and multiple copies increase the difficulty of locating corrupted data when verification fails, while fine-grained error localization is rarely explored. To tackle these challenges, we propose a lightweight certificateless public data auditing scheme for multi-copy and multi-cloud scenarios in a fog-assisted digital twin system, which supports batch auditing and block-level error localization. Both computational cost and communication overhead during verification remain constant, and are independent of the number of copies and data blocks. Furthermore, the error localization mechanism enables the accurate and rapid identification of malicious cloud servers, damaged copies, and corrupted data blocks, and supports data recovery without downloading any copies. The security analysis confirms the soundness and unforgeability of the proposed scheme. Performance evaluations and comparative analyses indicate that our scheme is efficient and practical.
- public data auditing,
- lightweight,
- certificateless,
- multi-cloud,
- multi-copy,
- fog-assisted digital twins
Citation: Pan Yang. Lightweight multi-copy public data auditing scheme with error localization for fog-assisted digital twins[J]. Big Data and Information Analytics, 2025, 9: 106-135. doi: 10.3934/bdia.2025006

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Abstract

The integrity and durability of digital twin data determine whether virtual models can meet the requirements of continuous prediction and maintenance of physical entities throughout their lifecycle. Unfortunately, existing cloud data auditing schemes fail to balance achieving lightweight public verification and low communication overhead in multi-cloud and multi-copy scenarios. Additionally, the dual factors of the existence of multiple cloud service providers and multiple copies increase the difficulty of locating corrupted data when verification fails, while fine-grained error localization is rarely explored. To tackle these challenges, we propose a lightweight certificateless public data auditing scheme for multi-copy and multi-cloud scenarios in a fog-assisted digital twin system, which supports batch auditing and block-level error localization. Both computational cost and communication overhead during verification remain constant, and are independent of the number of copies and data blocks. Furthermore, the error localization mechanism enables the accurate and rapid identification of malicious cloud servers, damaged copies, and corrupted data blocks, and supports data recovery without downloading any copies. The security analysis confirms the soundness and unforgeability of the proposed scheme. Performance evaluations and comparative analyses indicate that our scheme is efficient and practical.

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