Protecting Sensitive Data in an Evolving Digital Landscape

Introduction

The rise in data dimensionality with inexpensive storage is the prime factor for the extensive adoption of enterprise data-driven solutions for decision-making. The insights acquired from data points are evident in deriving business success. This realization has erupted with the data collection needs with an aim to capture every possible data point, ranging from general to personal and sensitive information.

The involvement of personal and sensitive data demands the implication of robust security measures on data at rest and in motion for protection. With the digital landscape being a vast terrain offering unlimited knowledge and services while withholding potential threats, it is crucial to leverage high-level data security systems to protect sensitive data and stay vigilant in the evolving digital realm to showcase integrity and ingenuity.

High-Level Data Security Practices

A comprehensive data protection strategy can be derived by leveraging the following systems and their capabilities  –  Unified Threat Management (UTM) and Data Loss Prevention (DLP). These practices are evolving and enable legacy and on-premise implementation of data protection.

An advanced and all-encompassing solution is Data Security Posture Management (DSPM). With robust data protection guarantees against vulnerabilities, DSPM use cases help evaluate the effectiveness of enterprise data security measures. The DSPM encompasses solutions and implementations against standard and custom security requirements by safeguarding the organization’s data assets from diverse threats.

These security systems are crafted carefully based on the modern needs to keep up with the evolving enterprise-grade security demands. Let us delve deeper and understand the characteristics and advantages of these data security systems.

Unified Threat Management (UTM) Systems

In the current cloud paradigm, secure exchange over the Internet mandates standard security measures adoption. To highlight, a few measures are firewalls, antivirus, security groups with inbound and outbound rules, network gateways, VPN, and more. These measures are robust, trustworthy, and effective for personal and commercial use.

Although the measures are proven effective, considering the depth of interconnected services and access levels for cloud-based data-centric applications, it becomes overwhelming to apply these measures to every data consumer or producer. Most critically, when sensitive or personal data are involved.

Acting as a unified hub to address modern data protection challenges, Unified Threat Management (UTM) is a solution that offers integrated security processes encompassing all highlighted protective measures.

Data Loss Prevention (DLP) Systems

Data level security takes precedence as the infrastructural and environmental security attributes can be addressed via Unified Threat Management. Oversharing, data spillage, and unauthorized data access are commonly observed data protection vulnerabilities in data at rest and motion.

Most data loss prevention solutions oversee enterprise-grade data monitoring and governance to prevent data loss and unauthorized access. This happens through carefully curated IAM and governance policies for fine-grained access controls enablement, sound encryption capabilities to protect data at rest and in transit, and custom solutions to monitor data consumer behavior and flag anomalies through incident response. These measures help enterprises protect data assets through secure data collaborations and be on par with compliance and regulations at a granular level.

Data Security Posture Management (DSPM)

UTM and DLP systems are mature and are proven worthy over time. The current digital landscape with a continuously evolving modern data stack and cloud adoption has many requirements outside the scope of these systems. Data being a foreign entity to most cloud-based applications, onboarding new data sources onto the platform needs risk, threat, and vulnerability assessment.

The assessment falls out of scope for UTM and DLP. Moreover, the data security measures applied on one system are generally transitioned to another for visibility, cross-reference, and custom integrations for custom logic implementation. Third-party systems exist to address the assessment and many other data security requirements. Onboarding various solutions introduces management and maintenance complexities into the applications that are costly and time-consuming.

DSPM systems equip the teams with processes for continuous assessment, monitoring, and safeguarding solutions to improve the overall data security posture. The DSPM delivers all security practices that are part of UTM and DLP, with assessments and security training under one umbrella. The key processes include data discovery and classification for perceiving the cardinality, correlation, and granularity to implement secure access controls and apply resilient vulnerability detection mechanisms with remediations. DSPM use cases are prominent in applying highly protective data security measures ranging from data governance to privacy and regulatory compliance.

Conclusion

Sensitive data entails personally identifiable information (PII) and preferences. If exposed to the wrong hands, the data can be used to manipulate and damage one’s reputation or financial condition. Protecting sensitive data is of the highest priority concerning the modern digital landscape.

Legacy systems such as UTM and DPL are picking up on the modern requirements by stepping into the cloud domain and diversifying the solution offerings. However, they lack several features and offer solutions in two different paradigms isolated from one another. In the current scenario, DSPM processes and use cases are the modern way to tackle data security challenges and protect the data against vulnerabilities and threats in the cloud realm.