Data Protection Cloud Gateways
Deploy a combination of forward/reverse proxy and API adapters to public cloud SaaS providers. They can apply encryption or tokenization to structured or unstructured data as it flows to the SaaS provider to mitigate inappropriate access that could lead to a breach. This helps meet data residency requirements for data protection and privacy. Functionality-wise, this ability is also provided by some security service edge (SSE) products.
Increasing volumes of sensitive data are stored across multiple public SaaS (software as a service) based tools, which increases the need to control data residency and access to data to mitigate security and privacy risks. CDPG (cloud data protection gateway) software is important to help reduce these risks by restricting access to data to specific staff, as well as potentially blocking access by the CSP (content security policy).
Secure Instant Communications
Typical regulations are the Health Insurance Portability and Accountability Act (HIPAA) and the regulations issued by the Financial Industry Regulatory Authority (FINRA).
Data Classification
Data classification is a process to classify the risk for data within all systems across organization, using factors like the value, security, access, usage, privacy, storage, ethics, quality, and retention requirements of the data. The higher the risk rating, the more precautions is required to securely manage the data. First step is needed to classify the sensitivity of the data so as to process and enable management and prioritization of data.
Classification and organization of information assets uses a process of categorization and finding relationships between business domains and subject areas. Because data classification is the process of organizing, it includes the application of tagging and labeling to a data object to facilitate its use and governance. This is done through the application of controls during its life cycle, or the activation of metadata using data fabric.
Data classification has an impact on a wide range of areas in data management, from identification, control and mitigation of risk in an application, and data security and compliance, to metadata management, master data management, content and records management, data stewardship, and multiple DataOps, among others.
Identifying and tagging all the organization’s data is the first step for maturity of data security and risk management. Increasing data classification capabilities in an organization also increases security and risk management capabilities. There are multiple automation and AI tools available for cloud and on-premises data-based applications.