From Cloud Data Sprawl to Cloud Data Security: Navigating the Complexities

Originally published by Dig Security.

Written by Sharon Farber.

More than 60% of enterprise data is now stored in the cloud. And as this number grows, it is becoming increasingly important to ensure complete data security. Cloud computing offers greater efficiency for storing, analyzing, and sharing data than on premises, but securing data across multiple platforms and services is no simple task and consequently, threats are on the rise. Organizations are often more vulnerable than they think and find themselves unprepared for attacks that get more sophisticated by the day. In fact, according to a 2021 survey, 98% of companies claimed they’d experienced a data breach within the last year and a half, which was up a significant 19% from the previous survey.

As such, it is more vital than ever for organizations to have full visibility and control over their data. This includes having the ability to:

• Locate and identify shadow data
• Reduce their attack surface
• Detect and respond to threats in real-time

This can be a daunting task, especially if you collect and store sensitive data such as PII, PHI, or PCI data that you must manage across multiple cloud providers and apply consistent policy to. Tracking and assessing security posture for data stored on disparate technologies is not only labor-intensive, but it gets risky when things like cloud data sprawl come into play as teams copy and move data around in their day-to-day work. This can have major implications as security controls put in place at the origin of the data – such as access controls, encryption and backup configurations – are no longer effective when it is moved to different locations.

To truly succeed, organizations must be able to discover, classify, protect, and govern their cloud data. There are numerous solutions that fail to offer data protection: legacy solutions that are not built for public clouds and its different deployments (PaaS and IaaS). The different cloud providers offer limited solutions that don’t expand to other clouds and provide visibility to only some of the assets. Finally, cloud security posture management (CSPM) solutions only focus on infrastructure security, and lack a data-centric view. None of these solutions provide full security for the modern complexities of data in the cloud to prevent data misuse, data exfiltration, and compliance breaches.

Instead, a cloud data-centric security model that combines data security posture management (DSPM), cloud data loss prevention (DLP), and data detection and response (DDR) – like can make tackling all of these issues simple.

• Data Security Posture Management (DSPM) highlights data misconfigurations, access anomalies, and data vulnerabilities. By accelerating assessments of how data security posture is enforced, it reduces business risk despite the speed, complexity, scale, and dynamics of multi-cloud.
• Cloud DLP prevents sensitive data from leaving an organization by monitoring and stopping exfiltration early in the kill chain.
• Real-Time Data Detection and Response (DDR) policy engine provides real-time detection and response to indicators of an active threat.