DB CyberTech Launches Intelligent Structured Data Classification to Identify PII

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According to a new press release, “DB CyberTech, a pioneer in machine learning based predictive data loss prevention, today announced advanced data classification for structured data as a new capability integrated across their security and compliance products. DB CyberTech’s intelligent data classification utilizes natural language processing to continuously and accurately identify an organization’s high-value sensitive data such as personal data, intellectual property, health records, and financial information. With this capability organizations are now able to focus security resources and compliance efforts on the specific set of databases that store sensitive data and therefore pose the greatest risk of loss to the organization. Advanced Data Classification is available now for DB CyberTech’s Predictive Data Loss Prevention and compliance solutions. The solution is offered with new cost effective software subscription pricing designed to enable small to large deployments as well as incremental deployments.”

The release goes on, “Data classification operates non-intrusively by analyzing database conversations in real time. No scanning or database login credentials are necessary and there’s no impact on performance. ‘High-value assets like personal information continue to be the focus for data theft and the need for predictive data loss prevention and intelligent data classification has never been greater. Many organizations have significant amounts of sensitive information on databases that have been completely forgotten,’ said Ali Hedayati, Senior Vice President, Corporate Strategy & Products of DB CyberTech. ‘When that happens it’s then unmaintained and not at all protected. This is evidenced by recent personal and high-value structured data losses at large enterprises. Once the data is lost, organizations struggle with their current solutions to detect the loss for a very long time – often for many months’.”

Read more at Release Wire.

Photo credit: DB CyberTech

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