Global IDs Sensitive Data Analysis and Identification Solutions
Sensitive data exposure and leakage attract regulatory scrutiny and may destroy the reputation of organizations. Larger organizations carry a bigger risk of unwanted or accidental data exposure from a random system, server, or person. People movement happens all the time.
Unless objectively asked, outgoing employees often don’t fully reveal what information they are carrying with them. Where and how they stored data, and whether that data contained sensitive information about employees or customers in isolation or in aggregation with other data sources.
What is Sensitive Data, and How can Global IDs Help?
Sensitive data refers to many categories of information that require special handling and protection to avoid unauthorized access, misuse, or disclosure. The most common types of sensitive information include personal information (e.g., race, religion, gender, sexual orientation), customer information (e.g., PII, purchase history), financial information (e.g., bank details, financial statements), Protected Health Information (e.g., diagnoses, health insurance), education records, and proprietary information (e.g., trade secrets).
Furthermore, the scope of sensitive data is constantly evolving. They can be biometric data such as fingerprints or handprints, geospatial coordinates, or criminal records. They can also be petabytes of graph data, machine-generated data, and wearables or IOT data. How can Global IDs help you detect and create a protective ring around sensitive information in an ever-expanding data landscape?
Global IDs Sensitive Data Analysis and Identification solution
Traditional token and pattern-based (regex etc.) sensitive data identification methods are no longer adequate. New and more complex data types frequently appear, and the scope of cyber crimes widens. While traditional methods require defining explicit rules to identify specific patterns or strings of characters that may indicate sensitive data, Global IDs’ proven methods leverage machine learning algorithms to learn from vast datasets and identify sensitive data based on their unique characteristics.
AI-based fingerprinting technology and data object-level detections offer a more accurate and efficient way of identifying sensitive information, particularly in complex data environments. Additionally, Global IDs’ methods can identify sensitive data that may not fit into traditional categories, providing a more comprehensive approach to data protection.
Using Global IDs’ Automated Data discovery processes, organizations can gain a high-level understanding of their data assets, paving the way for classifying data at various levels of security. This, in turn, leads to the discovery of sensitive data. AI-driven data discovery and risk analysis are executed across various data stores. Global IDs can validate the flow of information across the organization’s data landscape, providing visibility into the movement of sensitive data.
In addition, a real-time dashboard puts you in the driver’s seat, showing the locations of sensitive data elements and their potential risk. As new data is added to enterprise storage daily, the solution validates the new information in real-time. A dashboard provides qualitative information and suggests actions intuitively. With rich visualizations and detailed reports, risk free data sharing with third parties becomes possible. Compliance with data privacy and security regulations (CCPA, GDPR, PCI DSS, and HIPAA) becomes a part of the automation infrastructure.
Three Pillars of Global IDs Sensitive Data Identification Process
Enterprise-Wide Analysis for Remediation:
ML-driven scanners within the Global IDs software examine both structured and unstructured data on-premises and in the cloud, looking to identify Sensitive information. This helps data privacy/security teams to act on quick remediation while adhering to compliance programs.
An Accelerated Path to Compliance:
Armed with the Global IDs Sensitive Data Identification solution, organizations can quickly change their privacy and security postures. Enterprises may also periodically assess and update information security policies to counter new invisible threats.