Next DLP improves data protection using origin and movement

Insider risk and data protection biz Next DLP has unveiled its Secure Data Flow technology intended to improve protection for customers. Part of the supplier’s Reveal Platform, Secure Data Flow takes into account the origin, movement and modification of data to widen protection.

The tech, we’re told, can be used to secure the flow of critical business data from any SaaS application, including Salesforce, Workday, SAP, and GitHub, helping to prevent accidental loss and malicious theft.

John Stringer.

“In current IT environments, intellectual property commonly resides in an organization’s SaaS applications and cloud data stores,” said John Stringer, head of product at Next DLP. “The risk here is that high-impact data in these locations cannot be easily identified based on its content. Secure Data Flow, Reveal ensures firms can… protect their most critical data assets with confidence, regardless of their location or application.”

Next DLP claims legacy data protection technologies are “falling short”. It says they rely heavily on pattern matching, regular expressions, keywords, user-applied tags, and fingerprinting, which “can only cover a limited range of text-based data types”.

It adds that recent studies show employees download an average of 30 GB of data each month from SaaS applications to their endpoints, including mobile phones, laptops, and desktops, which underscores the need for advanced data protection measures.

By tracking data as it flows to sanctioned and unsanctioned channels within an organization, Secure Data Flow can “prevent data theft and misuse effectively”, through complementing traditional content and sensitivity classification-based approaches with origin-based data identification, manipulation detection, and data egress controls.

This results in an “all-encompassing, 100 percent effective, false-positive-free solution that simplifies the lives of security analysts,” claims Next DLP.

“Secure Data Flow is a novel approach to data protection and insider risk management,” said Ken Buckler, research director at analyst house Enterprise Management Associates. “It not only boosts detection and protection capabilities, but also streamlines the overall data management process, enhancing the fidelity of data sensitivity recognition and minimizing endpoint content inspection costs in today’s diverse technological environments.”