Aug 2026· International Journal of Computer Network and Information Security· 0 citations
TL;DR
A viable, privacy-friendly auditing framework of clouds which guarantees the end-toend encrypted verification without sacrificing the efficiency is presented.
Abstract
As the cloud computing and mass data sharing develop, data integrity and privacy has become an imperativeissue. Conventional remote data auditing techniques tend to reveal sensitive data or they have high computational cost.In order to overcome these shortcomings, the Fully Homomorphic Encryption enhanced Remote Method Invocation(FHEbRMI) mechanism that includes a combination of the Modified Least Squares (MLS) optimization model and theproposed cloud auditing security and efficiency are proposed in this paper. The suggested system provides an encrypteddata auditing system, which involves RMI-based communication, to enable the client, server, and third-party auditor toperform their verification functions remotely without the disclosure of the plaintext data. An actual execution of thesuggested structure is introduced, such as secure key generation, trapdoor-based dimensionality reduction, ciphertextmultiplication, and optimized homomorphic functions. Moreover, the RMI interface provides a smooth communicationamong the distributed nodes and increases the scalability and minimizes transmission delays. A comparative study withthe recent homomorphic-based auditing schemes like blockchain-assisted, certificateless and lattice-based FHE modelreveals that the proposed FHEbRMI-MLS model has better performance in terms of encryption/decryption latency,computational cost, and encryption overhead. The experimental performance is indicative of an average 37 and 42factor in speed of encryption and enhancement of computational efficiency respectively with respect to the traditionalFHE models. This paper presents a viable, privacy-friendly auditing framework of clouds which guarantees the end-toend encrypted verification without sacrificing the efficiency.
Keyword-based remote integrity auditing schemes effectively address the integrity of electronic medical records (EMRs) stored in the cloud. In practice, users expect to be able to perform flexible dynamic data updates while also protecting data privacy against a third-party auditor during the auditing process. However, existing schemes fail to simultaneously satisfy both requirements: they either incur prohibitive overhead for block-level updates or disclose to the auditor which EMRs match the target keyword and the number of such EMRs. To address this, we propose a new keyword-based auditing scheme for medical cloud. Specifically, we design a novel authentication identifier set. Unlike the keyword tags in Shen et al.’s scheme, this set aggregates the block hashes and thereby enables the auditor to verify integrity without obtaining sensitive information. Furthermore, we introduce a dynamic hash list. By updating this list during block insertion and deletion, the scheme eliminates the need to recompute the authenticators of subsequent blocks, significantly enhancing the efficiency of dynamic data updates. Security analysis confirms that the proposed scheme is secure. Performance analysis shows our scheme reduces block insertion and deletion overhead by over 60% compared to Gao et al.’s scheme, demonstrating high efficiency and practicality.
Meijuan Huang, Siyu Chen, Bo Yang et al.· Information· 0 citations
A novel VMKSE scheme (VMKSE-BFF) is presented by adopting BFF, which can simultaneously support verifiability of and secure data sharing in a multi-user setting and a comparison with the existing VMKSE schemes is provided.
Yandong Su, Bing-Hang Wang, Yan-Jie Xiang et al.· Mathematics· 0 citations
Cloud storage services have become a fundamental component of modern computing infrastructures, enabling scalable and cost-effective data management. However, outsourcing data to remote cloud servers introduces significant security challenges, particularly in ensuring data integrity, secure access control, and efficient auditing of stored information. Existing cloud auditing schemes primarily focus on integrity verification and often rely on trusted third-party auditors, leading to additional trust assumptions, communication overhead, and metadata management complexity. To address these limitations, this research presents a Kerberos-Assisted Secure Data Auditing Protocol (SDAP-K) that integrates authenticated service exchange with lightweight integrity verification for outsourced cloud storage. The proposed framework employs Kerberos-based mutual authentication and ticket-driven access control to establish secure communication among the Data Owner, Authentication Server, Metadata Server, and Cloud Data Server. To verify storage correctness, an N-ary hash tree with the Modified Murmur hash algorithm is used to enable efficient file- and block-level auditing without requiring a trusted third-party auditor. The framework further incorporates metadata-assisted auditing, dynamic data operations, and an error localization and recovery mechanism that identifies and restores corrupted data blocks. Security analysis demonstrates that the proposed protocol mitigates unauthorized access, replay attacks, impersonation attempts, and malicious data modification. Experimental results indicate that SDAP-K reduces storage execution time by 18.6%, retrieval time by 24.3%, update time by 21.8%, file-level auditing overhead by 31.5%, and block-level auditing latency by 36.2% compared with state-of-the-art research, while eliminating the need for a trusted third-party auditor. The results indicate that the proposed framework offers a practical, lightweight, and reliable solution for secure cloud data auditing in enterprise cloud storage environments.
Thangavel Murugan, Nasurudeen Ahamed Noor Mohamed Badusha, Priyan Malarvizhi Kumar et al.· Future Internet· 0 citations
Integrity auditing with data deduplication enables integrity verification of outsourced data on an untrusted cloud server while deduplicating identical data so that only a copy is stored for multiple clients. However, deriving the authenticator key from the file breaks the binding between the file and its owner. Conversely, generating authenticators under clients' secret keys leads to vulnerability to rogue public‐key attacks, or auditing costs that increase with the number of clients sharing the same file. In addition, existing schemes may reveal file ownership relationships to auditors or external adversaries, leading to privacy leakage. To address these problems, we propose an ownership‐unaware integrity auditing scheme with data deduplication. In our scheme, the cloud server stores only an aggregate authenticator and an aggregate public key for the same data. Meanwhile, both the proof generation and verification overheads remain independent of the number of clients. Moreover, our scheme hides client file ownership privacy from auditors and external adversaries. The security of our scheme can be reduced to the CDH assumption. In addition, performance evaluation indicates that the auditing cost remains constant regardless of the number of clients sharing the same file, making the scheme suitable for cloud storage systems.
Wenchao Wang, Bo Zhao, Haining Yang et al.· Concurrency and Computation· 0 citations
The findings indicate that unifying adaptive privacy preservation with decentralized integrity auditing yields a more complete cloud-security posture than either mechanism alone, and the paper outlines the empirical validation, including full-scale testbed experiments, required before deployment.
Jayakumar D, M. Ramamoorthy· International journal of com...· 0 citations
Integrating data deduplication with integrity auditing offers a practical approach to reducing cloud storage cost while safeguarding the integrity of outsourced data. Most of the existing schemes attempt to further reduce storage cost by performing authenticator deduplication on top of data deduplication. However, these schemes still require users to produce and upload the authenticators to the cloud for integrity verification. The generation of authenticators typically relies on BLS signature, which involves numerous costly exponentiation operations and requires bilinear pairing operations for verification. Moreover, most of these schemes risk leaking user file ownership information during the auditing process. In this paper, we propose a privacy-preserving deduplication and data integrity auditing scheme for compressed cloud storage. We design a novel encryption strategy wherein the users only perform lightweight algebraic operations to generate the file ciphertext. Based on this ciphertext, our scheme not only achieves data deduplication but also enables data integrity verification without relying on traditional authenticators, thereby significantly reducing storage and communication costs. In addition, we employ a randomized blinding technique to blind the file tag, auditing proof, and users’ public keys, effectively preventing the third-party auditor from inferring file ownership. Finally, we present comprehensive security analysis and experimental results to validate the security and efficiency of our scheme. Experimental results show that, compared with prior schemes, our scheme significantly reduces the computation cost in the initial upload phase, achieving up to a 2250-fold reduction. This improvement mainly stems from the use of lightweight algebraic operations. Furthermore, the proof generation process is accelerated by approximately 1480-fold, while the storage cost is reduced by up to 52%.
