By PJ Bradley

Technology moves at a pace that necessitates constant adaptation from threat actors and cybersecurity professionals alike to keep up with the rapid progress of the cyber landscape. Traditional methods of approaching cybersecurity and legacy data protection tools often grow outdated and ineffective over time as technology and threats evolve.

Data Security Posture Management (DSPM) is a relatively new approach to securing sensitive data in modern, complex digital environments. It accounts for many of the challenges of traditional data protection measures, incorporates the capabilities of several different legacy solutions, and ensures that security teams receive the support they need to enable them to carry out data protection and cybersecurity processes.

Changing Security Needs in Modern Digital Environments

Traditional security measures have often depended upon defining and protecting a border around the organization’s systems, which have historically been located on-premises and defended with measures like firewalls, access control, and tools for detecting intrusive activity. This approach to security has been able to protect against certain types of attacks, such as external actors attempting to infiltrate organizations.

However, this model of securing sensitive digital assets does not address threats like insider threats, whether they are malicious or unintentional. This approach has also lost effectiveness as many organizations have begun utilizing increasingly large and complex digital landscapes. The growing popularity of cloud platforms, remote and hybrid working environments, and artificial intelligence (AI) has created digital environments that are far more difficult to secure. Keeping outsiders out of a delineated area is insufficient for preventing threats.

This is an especially alarming trend in the case of data security, with data more spread out than ever before. Sensitive and crucial data is not only stored on-premises, but often dispersed throughout complex landscapes including multiple externally-hosted cloud platforms. Shadow data is an issue for many organizations, and traditional data security solutions are not equipped to discover and protect data across sprawling multi-cloud environments.

Core Functions of DSPM Tools

There are a number of major functions that DSPM platforms are designed to manage, many of which have traditionally been handled by standalone legacy solutions like data loss prevention (DLP), data lineage, and incident response. While “DSPM tools were not created equal” and do not all have the same functionality, some of the key capabilities of many DSPM solutions include:

• Data Discovery and Classification: Discovering data across all platforms, including IaaS, PaaS, and SaaS, and classifying it based on its access levels and sensitivity.
• Risk Assessment and Prioritization: Assessing the risk level and security posture of each data store and prioritizing the most pressing security tasks based on risk levels and threat trends.
• Configuration and Policy Management: Checking security settings for misconfigurations and ensuring that policies are built and enforced securely.
• Compliance Management: Identifying places where security posture and data protection measures are not aligned with industry standards and data security regulations.
• Incident Prevention and Remediation: Discovering vulnerabilities and threats to data security and facilitating risk mitigation and incident prevention tasks.
• Behavior Analytics: Establishing what normal user and entity activity looks like in order to detect anomalous behaviors that may indicate threat action.
• Continuous Monitoring and Reporting: Offering detailed reports and dashboards to provide visibility into data security postures and assist with documentation for compliance audits.
• Automation: Using advanced technology, including AI/ML, to automate some of the more repetitive, time-consuming, and labor-intensive tasks involved in data protection.

Advantages of Implementing DSPM

Implementing a DSPM tool can benefit organizations, especially those that have struggled to find adequate data security measures in the past. Many organizations can use DSPM tools to their advantage to take control of their digital environments, achieve visibility and insight into the security posture of their data stores, and establish and maintain regulatory compliance.

DSPM can help organizations prevent data breaches and the potentially catastrophic consequences associated with them, like financial losses, reputational damage, regulatory penalties, and even legal action. Protecting vast amounts of data across complex digital landscapes is difficult. Still, DSPM can enable security teams to secure sensitive data against sophisticated modern threats, mitigating many data security challenges in multi-cloud environments.

With the increasing adoption of AI technology and shadow data, DSPM is designed to assist organizations with sorting, evaluating, and protecting sensitive data, no matter where it is located. Unknown, undiscovered, and unstructured data stores are impossible to defend against threats, and DSPM helps provide visibility into not just where this data is located but also who has access to it, how it is used and changed, and its security posture.

Conclusion

Organizations may face difficulties in securing their sensitive data across modern digital landscapes that are only growing larger and more complex with time. DSPM is an approach that focuses on discovering, classifying, and protecting data throughout these sprawling environments, using advanced technologies to carry out a wide range of data security functions.

There are many steps involved in protecting data, and DSPM solutions aim to handle a great deal of the work that goes into this process. By carrying out tasks like classifying massive volumes of data and analyzing user behaviors, DSPM empowers security teams to effectively protect their organization’s sensitive data, improve their security postures, and maintain compliance with regulatory requirements.