Data security posture management

What is DSPM?

Data security posture management (DSPM) is a holistic approach to secure sensitive data. Traditionally, IT administrators have followed a system-centric approach and relied on legacy tools for data security. While the system-centric approach was invaluable in the past, it now struggles to keep pace with the proliferation of data and rapid growth in cloud adoption.

These shortcomings have given rise to the need for DSPM methodologies. DSPM adopts a data-centric approach, focusing on identifying and classifying sensitive data first before assessing and mitigating risks to that data and implementing security controls to maintain organizational security postures.

DSPM as defined by Gartner

Gartner has identified DSPM as a key emerging technology in its 2022 Hype Cycle for Data Security. The report highlights DSPM's capabilities in effectively mapping user access to datasets, tracking data lineage, and observing and protecting data, which are contributing to its growing adoption.

In their recent report "Innovation Insight: Data Security Posture Management (DSPM)" published in 2023, Gartner emphasizes several key points, including:

  • DSPM is a new and rapidly evolving market with promising potential.
  • It can help organizations address a variety of critical data security challenges.
  • Gartner recommends considering DSPM as an integral part of an overall data security strategy.

Based on these insights and predictions, it's likely that DSPM will play a significant role in enhancing data security in the coming years.

How does DSPM enhance overall security?

DSPM methodology places data at the forefront of security strategies and binds together the individual components of data security sequentially to assess and maintain your organization's security posture. The components required to maintain your security posture are:

  • Data discovery: This is the foremost component of any data security strategy. It involves discovering data across servers, endpoints, and the cloud. As data proliferates, and organizations use various applications to store data, the risk of shadow data will keep rising if your organization doesn't have proper systems to discover data. This is where DSPM solutions come in, any good DSPM solution discovers data across various sources and helps in minimizing shadow data.
  • Data classification: Classifying data based on sensitivity can help in implementing appropriate security measures for your organization's data. This is because classification tags function as pointers for data loss prevention (DLP) policies and response actions are chosen and executed based on whether a file is classified as Sensitive, Internal, Private, or Restricted.
  • Risk assessment and prioritization: Identifying risks to your data—such as violations of security policies, sensitive data being stored outside secure processing zones, or users with undue access to sensitive files—is vital to any security strategy. Grading users and files on a scale of 0 to 100 based on the risks identified can help in prioritizing and implementing security measures accordingly.
  • Remediation and prevention: This component strengthens your organization's security posture by reducing your attack surface and proactively mitigating potential risks. A DSPM solution that provides real-time alerts for suspicious activity, such as unauthorized permission changes on sensitive files or the detection of potential ransomware, can significantly improve your ability to prevent incidents.

The above stated components focus on particular aspects of data security; to maintain an effective security posture, it's essential for IT administrators to get each of these right.

DSPM use cases

DSPM's data-centric approach to security is leading to its rapid adoption across organizations. According to Gartner, more than 20% of organizations will deploy DSPM by the year 2026, "due to the urgent requirements to identify and locate previously unknown data repositories and to mitigate associated security and privacy risks." A few use cases of DSPM include:

  • Locating and protecting regulated and sensitive data

    As the volume of data organizations store across multiple channels increases, finding critical data amidst terabytes of shadow data can get tedious. This is where DSPM solutions come in, they discover sensitive data across various sources—such as cloud environment, on premise, and endpoints—and classify it based on sensitivity. This promotes better data hygiene and security.

    DataSecurity Plus' Data discovery and classification tool identifies sensitive data and provides you with comprehensive insights into the data you have, where it is located, and its sensitivity.

  • Achieving data access governance (DAG)

    Ensuring authorized users have access to data they require while preventing undue access to sensitive data can be tricky. DSPM solutions help you find users storing critical files, analyze users' permissions to those files, monitor attempts made to modify the files, and respond to anomalous accesses.

    DataSecurity Plus' File analysis helps you to detect sensitive files with open access and inconsistent permissions, while the file audit capability helps detect and respond to file access anomalies instantly.

  • Improving data privacy and compliance

    Data privacy regulations like HIPAA and the GDPR require organizations to continuously scan, analyze, and report on sensitive data locations and usage. This can have added complexity when dealing with large, dynamic volumes of data. Since DSPM tools automate this process along with considerations such as incremental scanning to reduce impact on storage performance and availability, DSPM can help organizations track data lineage and identify where sensitive data resides, making it easier to comply with privacy regulations.

    DataSecurity Plus' compliance reporting capability can help in adhering to the GDPR, PCI DSS, SOX, and other data privacy regulations.

  • Preventing data leaks

    DSPM solutions take a holistic, data-centric approach to DLP. This starts from identifying users with access to sensitive data, audit attempts made to access this data, regulate data flow, and manage external devices and web applications to prevent data leaks.

    DataSecurity Plus's data leak prevention tool allows you to configure DLP policies that can help you track and control data flow across various sources such as web, email, USBs, and on-premise devices.

Empower your data security journey with DSPM

DataSecurity Plus helps put your DSPM strategy to play by providing holistic insights into your data and identifying risks, allowing you to craft incident response policies and build a robust security posture. See how it can work for you.

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