Pierluigi Paganini
October 23, 2024
Data Security Posture Management (DSPM) comes into play– an essential solution for addressing evolving data security and privacy requirements
Data plays a significant role and will continue to do so in the future. Consider the cloud environment, where migrating workloads is a norm. However, the proliferation of such workloads and the data within creates a complex web of data sprawl that is challenging to navigate and manage. It becomes increasingly difficult to gain complete visibility or transparency that could help security and privacy teams discover sensitive data, identify its security and compliance postures, and mitigate risks.
To add to the difficulty, the advent of Generative AI (GenAI) has brought unprecedented security and privacy risks. Accompanying these risks is the obligation to comply with the emerging AI laws that necessitate enhanced handling of sensitive data in GenAI pipelines. Teams must identify and accurately classify sensitive data to ensure enhanced security, privacy, and compliance posture.
Here, Data Security Posture Management (DSPM) comes into play– an essential solution for addressing evolving data security and privacy requirements.
Data Security Posture Management, also known as DSPM, is a relatively new term first coined by Gartner in its 2022 Hype Cycle™ for Data Security report. The report highlighted the heightened risks of increasing multi-cloud adoption, growing data volumes, and the dire need for a data-centric approach to cloud data security. Building upon the same concept, GigaOm rolled out its first-ever DSPM vendor evaluation report, defining DSPM as a tool that offers “visibility into where sensitive data is, who has access to it, and how it is being used. DSPM gives a comprehensive view of an organization’s data security posture, compliance position, security and privacy risks, and how to deal with them.”
With this principle approach, DSPM treats data security as a priority, aligning itself with the critical security standards and frameworks and further addressing the regulatory requirements of current and emerging data and AI laws that necessitate implementing personal and sensitive personal data protection measures.
Looking back at the definition of the GigaOm Radar report, DSPM allows organizations to seek answers to the most pressing questions of security and privacy teams:
The latest statistics reveal that approximately 402.74 million terabytes of data are created daily. According to other reports, most of that data is unstructured. As organizations deal with such high volumes of dark and unstructured data, most of this data contains sensitive information, making it a primary target for data breach attacks. Consequently, organizations face various security, governance, privacy, and compliance risks.
Let’s examine some of the concerning factors that require a robust DSPM solution.
Let’s examine some of the major data privacy frameworks and how data security posture management enables organizations to discover and classify data, alert on privacy gaps, and help ensure an enhanced privacy posture.
The European Union’s General Data Protection Regulation (EU GDPR) offers a data privacy framework that applies to both EU and non-EU businesses. It establishes strict data privacy and security standards that have inspired the global data privacy laws that we see today. For instance, the regulation requires organizations to ensure purpose limitation and data minimization. These principles mandate that organizations collect only data necessary to serve the purpose for which it is initially collected. GDPR further provides multiple data subject rights, which requires organizations to correct any inaccuracies in data timely, delete it, or impose retention policies.
DSPM can play a significant role in helping organizations align their data privacy operations with the GDPR provisions. For instance, organizations can leverage DSPM to detect and catalog personally identifiable information (PII) spread across the organization’s data stores, SaaS services, or multi-cloud accounts. Similarly, GDPR also places great emphasis on implementing measures to prevent unauthorized access or sensitive data exposure. Here, DSPM can provide organizations insights into access entitlements, allowing organizations to establish access policies based on either users, roles, or permissions and ensure least privilege access. DSPM also provides visibility of security and privacy posture, alerting potential gaps.
HIPAA is a compliance framework designed to protect patients’ health information in the United States. The framework covers patients’ protected health information (PHI), including a patient’s name, address, health records and history, social security number, etc. The act requires covered entities to establish appropriate access control, data sharing policies, and audit control. DSPM can help covered entities to comply with HIPAA regulations by identifying PHI across an entities’ data stores, SaaS services, and other cloud environments. DSPM can further help the entities ensure that the data assets containing patients’ PHI has appropriate security measures, such as access policies and controls, etc.
DSPM is a necessary tool in an organization’s data management and protection arsenal. However, it is important that DSPM should be implemented as an integration to an organization’s existing data command center rather than a siloed module.
About Author: Anas Baig
With a passion for working on disruptive products, Anas Baig is currently working as a Product Manager at the Silicon Valley based company – Securiti.ai. He holds a degree of Computer Science from Iqra University and specializes in Information Security & Data Privacy.
Follow me on Twitter: @securityaffairs and Facebook and Mastodon
(SecurityAffairs – hacking, DSPM)
