Data protection has always been one of the most crucial areas in cybersecurity, a significant priority for many organizations, especially those in heavily targeted and highly regulated industries such as finance, healthcare, law, education, and government. There is a long-established framework for protecting sensitive data that focuses on keeping outsiders out as the main measure against threats, but modern digital environments have rendered this approach obsolete.
Data Security Posture Management (DSPM) “is particularly effective in securing sensitive information across a multitude of data stores.” As a relatively recent development in protecting sensitive data, it is designed to specifically account for the evolution of the digital landscape and data dispersed across broad attack surfaces. This method of addressing data security shifts the focus to look at the data itself and obtain insights for protecting it wherever it is stored.
Traditional “Castle and Moat” Security Paradigm
The longstanding tradition in cybersecurity has been built on the “castle and moat” model, which positions an organization’s systems and assets as existing fully within a protected area with a clear perimeter. Securing this perimeter is the priority in this paradigm, and many organizations take steps to fortify these measures rather than update their security strategies for modern needs.
This traditional approach rests on a few data security assumptions that are outdated at best: that an organization’s sensitive data will be contained within a designated perimeter, that those within the organization are trustworthy and threat actors will be outside of the perimeter, and that keeping them out is sufficient to prevent data loss. In modern digital landscapes, none of these facts can be taken for granted, and this approach to security is not effective against evolving threats.
Measures used to secure these walls and keep unauthorized users out include firewalls, access control, and intrusion detection. These tools are fairly effective at keeping outsiders out of a given network or area, but they fail to account for other sources of risk to data, especially in a modern digital environment with multiple cloud platforms.
Modern Needs for a Data-Focused Security Approach
With the growth of cloud infrastructure, many organizations store data across much broader attack surfaces, including externally hosted cloud platforms. This means that there is no longer a defined perimeter around an organization’s data stores that can be secured and fortified against intruders. The increasing popularity of remote and hybrid working environments has created a landscape where sensitive data and authorized users alike are spread out rather than contained within on-premises systems.
Insider threats are always a danger, including malicious internal actors, user error, and compromised insider accounts or devices. Any employee with authorized access to sensitive areas could be a source of unintentional risk to data by falling for a phishing attack, making a typo in an email address, or having their account compromised by threat actors. Organizations using security measures that depend solely on identity-based access control are not adequately protected against internal risks.
Security tools that are restricted to searching specific systems, data stores, and network areas are not equipped to protect sensitive data in modern environments effectively. Shadow data is a significant source of risk for many organizations, and traditional security tools are not built to discover this unknown data. Identifying and classifying vast amounts of data across broad, complex digital environments is a difficult task in itself, and that is only the beginning of ensuring data security.
The rapid adoption of new technologies like Artificial Intelligence (AI) and Machine Learning (ML) has also created new security vulnerabilities for many organizations and enhanced cybercriminal tactics like phishing attacks to increase success rates and payouts. New developments and constantly shifting threat trends require an updated and adaptable approach to securing sensitive data.
DSPM Shifting the Focus of Data Security
DSPM is a data-focused approach to securing modern digital environments. Rather than searching known and specified areas for threats, it is designed to discover and protect data across complex and multi-cloud environments.
A variety of functions traditionally handled by standalone tools can be covered in one DSPM platform, including:
- Data Discovery and Classification: Finding data across all cloud platforms, including shadow data, and classifying it according to factors like access and sensitivity levels.
- Risk Assessment and Prioritization: Evaluating the risk level and security posture of data stores and prioritizing security tasks based on risk levels and most pressing threats.
- Configuration, Policy, and Compliance Management: Ensuring that security settings and policies are configured and enforced securely and that data protection measures align with regulatory requirements.
- Incident Detection, Remediation, and Prevention: Identifying threats to data security and providing visibility and insight to prevent and mitigate security incidents.
- Continuous Monitoring, Reporting, and Alerting: Providing detailed reports and dashboards for organizations to improve the security posture of their data stores and aid in documenting compliance.
- User and Entity Behavior Analytics: Using advanced techniques like AI/ML to establish a baseline of normal behavior in order to detect anomalous activity that could indicate a threat.
Conclusions
Traditional methods of protecting data have become increasingly outdated over the years as organizations’ digital landscapes have evolved to be more spread out and externally hosted. Legacy tools and measures can effectively carry out some aspects of data protection, like access management or incident response, but none provide comprehensive data-focused security.
DSPM was developed to address modern threats to data stored across complex cloud environments. It enables a data-first approach to every step of data protection, from discovery to incident response. By focusing on the data, DSPM solutions help ensure comprehensive data security in complex digital environments.
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