Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{145818,
        author = {R Jothi},
        title = {Dynamic and Public Auditing with Fair Arbitration for Cloud Data},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {11},
        pages = {524-530},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145818},
        abstract = {Cloud users no longer physically possess their data, so how to ensure the integrity of their outsourced data becomes a challenging task. Recently proposed schemes such as “provable data possession” and “proofs of retrievability” are designed to address this problem, but they are designed to audit static archive data and therefore lack of data dynamics support. Moreover, threat models in these schemes usually assume an honest data owner and focus on detecting a dishonest cloud service provider despite the fact that clients may also misbehave. This paper proposes a public auditing scheme with data dynamics support and fairness arbitration of potential disputes. In particular, we design an index switcher to eliminate the limitation of index usage in tag computation in current schemes and achieve efficient handling of data dynamics. To address the fairness problem so that no party can misbehave without being detected, we further extend existing threat models and adopt signature exchange idea to design fair arbitration protocols, so that any possible dispute can be fairly settled. The security analysis shows our scheme is provably secure, and the performance evaluation demonstrates the overhead of data dynamics and dispute arbitration are reasonable.},
        keywords = {Integrity auditing, public verifiability, dynamic update, arbitration, fairness.},
        month = {},
        }