面向多租户云平台知识产权保护的安全AI水印框架
Secure AI Watermarking Framework for IP Protection in Multi-Tenant Cloud Platforms
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中文总结 AI 辅助
针对多租户云平台的AI知识产权泄露问题，提出基于密钥认证的安全AI水印框架，结合主动与被动安全措施，可预防攻击并识别联邦学习等场景下的IP泄露。
中文摘要 AI 辅助
随着基于云的AI服务的扩展，在私有受保护认证平台上运行的多租户环境中的安全数据防护交易应运而生。为解决安全泄露问题，我们提出一种安全AI水印系统，该系统基于密钥认证在可信方之间分配密钥，可指导主动与被动安全警报系统的安全防护方式，通过主动措施在攻击发生前进行预防。该系统具有基于域的限制和有限访问权限，其被动方法可捕获水印和生物特征识别，用于识别在联邦学习与远程学习算法的数据和模型交换过程中发生的特定于所有者设备的知识产权泄露。
英文摘要
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.
发表机构
- Viswam Engineering College（维斯瓦姆工程学院）
- Mother Theresa Institute Of Engineering and Technology（特蕾莎修女工程技术学院）
- Mohan Babu University（莫汉·巴布大学）
机构由 AI 辅助整理，请以论文原文为准。
