Data Classification: A Core Component of DSPM

Imagine a library where the books are shelved without appropriate categorization or classification. In such a place, finding a specific book from a specific genre can be a daunting challenge, even for a librarian. The same is true for DSPM and Data Classification.

A data security posture management solution may operate blindly if it lacks a strong understanding of data. Data security and management begin with knowing what data is sensitive, business-critical, or subject to regulation. For instance, a security tool may detect an exposed S3 bucket. However, it wouldn’t be able to determine the remediation priority if the sensitivity of the asset isn’t known.

Here, data classification plays a crucial role in promoting sensitive data literacy throughout a corporate data environment.

Read on to learn more about the integral role of data classification in powering DSPM.

Why Data Classification is Essential in DSPM

DSPM, as comprehensively discussed in our blog 'What’s DSPM,' is a data-centric solution that provides an overall picture of your data landscape, assesses security posture for risks, and automates remediation. It offers a proactive approach to data protection that goes a long way in securing sensitive data across hybrid, multicloud environments.

With the growing number of challenges organizations face today, such as multicloud complexity, data sprawl, shadow data, and a lack of visibility into sensitive data access, DSPM is a critical requirement for overcoming them. However, DSPM in itself isn’t complete without a robust and accurate data classification engine. There are several reasons why data visibility, as offered by DSPM, is not sufficient to protect data efficiently on its own.

DSPM solutions can seamlessly integrate with a wide range of data lakes, data warehouses, or cloud repositories to detect sensitive data, such as personal information. However, without any data context, security teams may fail to identify the exact type of data and protect it effectively.

For instance, a series of numbers on a spreadsheet could be anything, from an employee's phone number to a customer’s Social Security Number (SSN). A lack of data context can hinder a security team’s ability to accurately define sensitive data, establish effective security policies, or implement remediation measures.

Similarly, data context regarding jurisdiction is also critical in meeting compliance requirements. For instance, data protection laws pose different requirements on business owners for data management and security, including notification requirements in the event of a breach. For that, organizations have a clear understanding of the data elements, who the data belongs to, and which notification laws are applicable. Timely and accurate breach notifications can prevent both legal implications and reputational damage.

Similarly, data sovereignty and localization laws differ across jurisdictions. Organizations must exercise special care when transferring data to other jurisdictions, given the stringent requirements for cross-border data transfers. Here, data classification can help understand what data is subject to localization or cross-border data laws by categorizing it based on location, data type, and applicable regulations. With additional labeling, privacy teams can enforce specific policies that could notify of improper data transfers.

How Data Classification Drives Core DSPM Capabilities

Let’s take a closer look at how data classification contributes to some of the core capabilities of DSPM.

Risk Prioritization

Organizations contain different types of data. Some datasets contain trivial information and are thus categorized as public data. Datasets that contain intellectual property (IP) information are categorized as sensitive data because they involve trade secrets, patents, and other confidential information. Data classification helps DSPM to distinguish between a public dataset containing a trivial marketing deck and an exposed bucket containing unencrypted financial data. This triage further assists teams in risk scoring and thus prioritizing high-risk assets.

Policy Enforcement

One of the key functions of DSPMs is to enforce effective policies around data security, governance, privacy, and compliance. With the classification defining each data element with accurate labels, such as “PII,” “PHI,” or “Confidential,” organizations can ensure that effective measures against security and compliance risks are applied. Based on the policy, the DSPM platform can trigger the appropriate controls accordingly, such as encryption, quarantine, masking, etc.

Access Controls Enforcement

Data classification plays a critical role in empowering DSPM’s Data Access Intelligence and Controls capabilities. The categorization capability can help access teams tailor the access policies and controls of datasets according to their sensitivity. For instance, sensitive PII can be restricted to specific users or roles that are authorized to access such data. Similarly, automated access policies can also be enforced to either revoke a user’s access to sensitive data or mask it for secure sharing.

Safe GenAI Applications

GenAI applications, such as copilots, are rapidly gaining dominance in the tech industry. In fact, 70% of Microsoft’s employees reported increased productivity in the Microsoft 365 Copilot Early Access Program. Since such AI-powered conversational assistants can access files and data indiscriminately across an enterprise environment, they could expose sensitive information to unauthorized users. Data classification can help enterprises prevent unintended access to sensitive data by labeling and protecting it at very granular levels. With sensitive data labeling, enterprises can enforce policies and controls restricting the AI copilot from accessing sensitive data.

Examples of DSPM Leveraging Data Classification

The need for a modern DSPM with integrated data classification can be best understood by examining some industry-specific examples.

• Any healthcare institution, such as hospitals, dealing with electronic protected health information (ePHI) is required to adhere to the Health Insurance Portability and Accountability Act (HIPAA). DSPM with integrated data classification can help identify ePHI data across a healthcare institution’s data environment and categorize it according to HIPAA and similar healthcare laws for compliance.
• Financial information, such as PINs, credit card numbers, or bank account details, is all protected under the Payment Card Industry Data Security Standard (PCI DSS) framework. DSPM can help financial institutions discover and categorize all the data associated with payment processing. By leveraging that data, organizations can effectively implement appropriate controls to protect PCI DSS-regulated data, such as encryption.
• Similarly, government entities are also required to manage and protect citizens’ personally identifiable information (PII) under the GDPR. DSPM platforms can help government entities accurately classify PII and ensure compliance with the GDPR.

Discover and Classify Data at Scale with Securiti’s DSPM Platform

Securiti’s DSPM solution offers powerful AI-powered data discovery and classification capabilities. The platform integrates with a breadth of data systems and applications, discovering both native and shadow data across structured and unstructured formats. The classification engine leverages advanced NLP/ML algorithms and a rich set of out-of-the-box classifiers to categorize and label a wide range of data types, including but not limited to PII, PHI, financial data, as well as data in unstructured formats like audio and video data.

Ready to see Securiti’s data discovery and classification capabilities in action? Schedule a demo now.