为多租户云平台设计可防泄露的AI水印框架，保护知识产权。
Secure AI Watermarking Framework for IP Protection in Multi-Tenant Cloud Platforms
- 基于可信方分发密钥，实现主动防御水印机制。
- 在联邦与远程学习中检测数据模型交换时的侵权行为。
- 适合需要版权保护的云AI服务提供商使用。
随着基于云的AI服务扩展，多租户环境下的安全数据交易面临泄露风险。本文提出一种安全AI水印框架，通过可信方间分发密钥，并结合身份认证机制，构建主动与被动双重安全预警系统。该系统可在攻击发生前通过主动措施进行防护，限制访问权限并实施域内运行约束。同时，针对联邦学习和远程学习中的数据与模型交换过程，该系统能有效识别基于生物特征的身份信息及知识产权泄露行为，保障多方协作场景下的版权安全。
原文摘要 · Abstract (English)
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.
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