Secure AI Watermarking Framework for IP Protection in Multi-Tenant Cloud Platforms
A new research paper proposes a secure AI watermarking framework designed to protect intellectual property in multi-tenant cloud platforms. The framework integrates key distribution among trusted parties and employs both proactive and reactive security measures. Proactive measures include domain-based access restrictions, while reactive methods utilize watermarking and biometric identification to trace IP leakage during data and model exchange in federated and remote learning. The paper is available on arXiv under the identifier 2608.02656, categorized under Cryptography and Security.
Key facts
- The paper is titled 'Secure AI Watermarking Framework for IP Protection in Multi-Tenant Cloud Platforms'.
- It addresses IP leakage challenges in cloud-based AI services.
- The framework uses key authentication distributed among trusted parties.
- It includes both proactive and reactive security alert systems.
- Proactive measures involve domain-based restrictions with limited access.
- Reactive methods use watermarking and biometric identification.
- The framework targets IP leakage during federated and remote learning.
- The paper is available on arXiv with identifier 2608.02656.
Entities
Institutions
- arXiv