Insider risk and data protection company Next DLP has unveiled its new Secure Data Flow technology, designed to enhance data protection for customers. Integrated into the company’s Reveal Platform, Secure Data Flow monitors the origin, movement, and modification of data to provide comprehensive protection. Data Protection Improvements from Next DLP.

This technology can secure critical business data flow from any SaaS application, including Salesforce, Workday, SAP, and GitHub, to prevent accidental data loss and malicious theft.

“In modern IT environments, intellectual property often resides in SaaS applications and cloud data stores,” said John Stringer, head of product at Next DLP. “The challenge is that identifying high-impact data in these locations based on its content is difficult. Secure Data Flow, through Reveal, ensures that firms can confidently protect their most critical data assets, regardless of their location or application.”

Next DLP argues that legacy data protection technologies are inadequate, relying on pattern matching, regular expressions, keywords, user-applied tags, and fingerprinting, which only cover a limited range of text-based data types.

The company highlights that recent studies indicate employees download an average of 30 GB of data each month from SaaS applications to their endpoints, such as mobile phones, laptops, and desktops, emphasizing the need for advanced data protection measures.

Secure Data Flow tracks data as it moves through both sanctioned and unsanctioned channels within an organization. By complementing traditional content and sensitivity classification-based approaches with origin-based data identification, manipulation detection, and data egress controls, it effectively prevents data theft and misuse.

This approach 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 represents a novel approach to data protection and insider risk management,” said Ken Buckler, research director at Enterprise Management Associates. “It not only enhances detection and protection capabilities but also streamlines data management processes. This improves the accuracy of data sensitivity recognition and reduces endpoint content inspection costs in today’s diverse technological environments.”

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