论文标题
关于共享，沟通和计算环境的数据保护的整体观点：分类和未来方向
A Holistic View on Data Protection for Sharing, Communicating, and Computing Environments: Taxonomy and Future Directions
论文作者
论文摘要
数据是组织的重要资产，必须确保该资产安全至关重要。它需要在任何状态下的安全性，即剩余数据，使用中的数据和运输中的数据。当包含第三方时，即当数据存储在云中时，需要更加注意它，然后需要更多的安全性。由于机密数据可以驻留在各种计算设备上（物理服务器，虚拟服务器，数据库，文件服务器，PC，销售点设备，闪光灯驱动器和移动设备），并通过各种网络访问点（Wireline，无线，无线，VPN等）移动，因此解决方案或机制需要解决数据丢失的解决方案或机制删除数据损失数据丢失，数据删除数据删除数据和数据数据删除。在这种情况下，本文为任何类型的组织提供了共享和交流环境的数据保护的整体观点。讨论了在保护机密数据时面临的数据泄漏保护系统的分类法和主要挑战。数据保护解决方案，数据泄漏保护系统的分析技术以及对赋予基于机器学习的方法的现有最新贡献的彻底分析。最后，本文探讨并结论了有关数据保护的各种关键新兴挑战和未来的研究方向。
The data is an important asset of an organization and it is essential to keep this asset secure. It requires security in whatever state is it i.e. data at rest, data in use, and data in transit. There is a need to pay more attention to it when the third party is included i.e. when the data is stored in the cloud then it requires more security. Since confidential data can reside on a variety of computing devices (physical servers, virtual servers, databases, file servers, PCs, point-of-sale devices, flash drives, and mobile devices) and move through a variety of network access points (wireline, wireless, VPNs, etc.), there is a need of solutions or mechanism that can tackle the problem of data loss, data recovery and data leaks. In this context, the paper presents a holistic view of data protection for sharing and communicating environments for any type of organization. A taxonomy of data leakage protection systems and major challenges faced while protecting confidential data are discussed. Data protection solutions, Data Leakage Protection System's analysis techniques, and, a thorough analysis of existing state-of-the-art contributions empowering machine learning-based approaches are entailed. Finally, the paper explores and concludes various critical emerging challenges and future research directions concerning data protection.
