Secure AI Watermarking Framework for IP Protection in Multi-Tenant Cloud Platforms

The Secured data safe guard transaction with multi-tenant environments run on private-protected authenticate platforms runs by secured handed environments that emerges with the expansion of cloud-based AI services. To enhanced this secured leakage address challenges solution to protect a secure AI Watermarking system incorporating key distributed between trusted parties based on key authentication as we proposed solution to guided safe guarded way to reactive, and proactive security alert systems using algorithms. This proposed system before attacks can be prevented through the active measures. domain run base restrictions with limited access. Conversely, Proposed system reactive methods to captured on watermarking and biometric identification owner device specific IP leakage that occur during the exchange of data and models in federated and remote learning algorithms.

  • Research Type: Action Research
  • Paper Type: Experimental Research Paper
  • Vol.7 , Issue 6 , Pages: 69 - 82, Nov 2025
  • Published on: 15 Nov, 2025
  • Issue Type: Regular
  • Cite Score
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    100

  • No. of authors
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    75

  • No. of Downloads
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    43

  • Cite Score
    :

    100

  • No. of authors
    :

    75

  • No. of Downloads
    :

    43

  • Cite Score
    :

    100

  • No. of authors
    :

    75

  • No. of Downloads
    :

    43

About Authors:
M. Anjankumar
India
Viswam Engineering College

""""


Prathima Chilukuri
India
Mohan Babu University

..


Copyright © 2025, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Corresponding Author: M. Anjankumar, anjanind@gmail.com

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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