FairCMS：具有公平版权保护的云媒体共享
FairCMS: Cloud Media Sharing with Fair Copyright Protection
AI总结：
针对云媒体共享中的数据隐私、版权和用户权利保护问题，提出两种基于代理重加密和非对称指纹的方案 FairCMS-I 和 FairCMS-II，在效率与安全上提供不同权衡，并经实验验证可行。
摘要：
繁重的媒体共享任务促使资源受限的媒体所有者向云平台寻求帮助，即将媒体内容存储在云中并让云进行共享。在云媒体共享场景中，有三个关键的安全/隐私问题需要解决，包括云中的数据隐私泄露和访问控制、对所有者版权的侵犯以及对用户权利的侵犯。鉴于没有单一技术能同时解决上述三个问题，本文提出了两种云媒体共享方案，分别命名为 FairCMS-I 和 FairCMS-II。通过巧妙地利用代理重加密技术和非对称指纹技术，FairCMS-I 和 FairCMS-II 以不同的隐私/效率权衡解决了上述三个问题。其中，FairCMS-I 更侧重于云端效率，而 FairCMS-II 更侧重于媒体内容的安全性，这为所有者提供了灵活的选择。此外，在可选的 IND-CPA（选择明文攻击下的不可区分性）安全性和高云端效率，以及免除对可信第三方的需求方面，FairCMS-I 和 FairCMS-II 也优于现有的云媒体共享方案。另外，FairCMS-I 和 FairCMS-II 允许所有者获得显著的本地资源节省，因此可以被视为非对称指纹的隐私保护外包。最后，实验证明了 FairCMS-I 和 FairCMS-II 的可行性和效率。
英文摘要：
The onerous media sharing task prompts resource-constrained media owners to seek help from a cloud platform, i.e., storing media contents in the cloud and letting the cloud do the sharing. There are three key security/privacy problems that need to be solved in the cloud media sharing scenario, including data privacy leakage and access control in the cloud, infringement on the owner's copyright, and infringement on the user's rights. In view of the fact that no single technique can solve the above three problems simultaneously, two cloud media sharing schemes are proposed in this paper, named FairCMS-I and FairCMS-II. By cleverly utilizing the proxy re-encryption technique and the asymmetric fingerprinting technique, FairCMS-I and FairCMS-II solve the above three problems with different privacy/efficiency trade-offs. Among them, FairCMS-I focuses more on cloud-side efficiency while FairCMS-II focuses more on the security of the media content, which provides owners with flexibility of choice. In addition, FairCMS-I and FairCMS-II also have advantages over existing cloud media sharing efforts in terms of optional IND-CPA (indistinguishability under chosen-plaintext attack) security and high cloud-side efficiency, as well as exemption from needing a trusted third party. Furthermore, FairCMS-I and FairCMS-II allow owners to reap significant local resource savings and thus can be seen as the privacy-preserving outsourcing of asymmetric fingerprinting. Finally, the feasibility and efficiency of FairCMS-I and FairCMS-II are demonstrated by experiments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
