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.
翻译:由于机密数据可以存放在各种计算机装置上(物理服务器、虚拟服务器、数据库、文件服务器、个人计算机、销售点装置、闪存器和移动装置),并且通过各种网络接入点(网络、无线、VPNs等)移动,因此,无论该数据在休息、使用中的数据和中转中的数据,都需要在包括第三方时,即当数据储存在云中时,需要更多注意这些数据,因此需要更加安全;由于机密数据可以存放在各种计算机装置上(物理服务器、虚拟服务器、数据库、文件服务器、文件服务器、个人计算机、销售点装置、闪存器和移动装置),并且需要安全,无论它是在何种状态下,都需要安全;需要有更多的解决办法或机制来处理数据丢失、数据恢复和数据泄漏问题;在这方面,本文件提出了为任何类型的组织共享和交流环境而保护数据的整体保护观点;讨论了数据渗漏保护系统分类和在保护机密数据时所面临的重大挑战;数据保护系统的分析技术、数据渗漏保护系统的分析技术,以及对现有状态和最新贡献增强关键研究方向和今后研究方法的透彻分析。