mlsanityData to 13 Oct 2026

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

arXiv 2608.02656 ↗First posted 1 Aug 2026cs.CR cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 11 of its 31 references that are in the map. First posted on arXiv 1 Aug 2026.

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11 of 31 references.

References · 11

  1. 2018Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooringcited by 356
  2. 2017Machine Learning Models that Remember Too Muchcited by 169
  3. 2017Adversarial Frontier Stitching for Remote Neural Network Watermarkingcited by 118
  4. 2019DAWN: Dynamic Adversarial Watermarking of Neural Networkscited by 99
  5. 2019Deep Neural Network Fingerprinting by Conferrable Adversarial Examplescited by 93
  6. 2019Robust Watermarking of Neural Network with Exponential Weightingcited by 51
  7. 2020Passport-aware Normalization for Deep Model Protectioncited by 43
  8. 2021Reversible Watermarking in Deep Convolutional Neural Networks for Integrity Authenticationcited by 17
  9. 2019Evolutionary Trigger Set Generation for DNN Black-Box Watermarkingcited by 6
  10. 2018Performance Comparison of Contemporary DNN Watermarking Techniquescited by 5
  11. 2019MimosaNet: An Unrobust Neural Network Preventing Model Stealingcited by 2

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  1. 2023Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks
  2. 2022Device-Bind Key-Storageless Hardware AI Model IP Protection: A PUF and Permute-Diffusion Encryption-Enabled Approach
  3. 2025NWaaS: A Non-Intrusive and Privacy-Preserving Watermarking-as-a-Service System with Adaptive Resource Scheduling
  4. 2023FedCIP: Federated Client Intellectual Property Protection with Traitor Tracking
  5. 2022Watermarking in Secure Federated Learning: A Verification Framework Based on Client-Side Backdooring
  6. 2023Who Leaked the Model? Tracking IP Infringers in Accountable Federated Learning
  7. 2025CHIP: Chameleon Hash-based Irreversible Passport for Robust Deep Model Ownership Verification and Active Usage Control
  8. 2024Agentic Copyright Watermarking against Adversarial Evidence Forgery with Purification-Agnostic Curriculum Proxy Learning