Titus

Smarter Data Protection with Machine Learning.

Whitepaper

With the explosion of unstructured data, many organizations seek ways to enhance their data protection strategies for better privacy and stronger security against cyberthreats. However, many companies struggle to accurately identify complex data as it moves through their user workflows. It’s difficult to protect something if you don’t know you have it.

Manual processes for identifying, classifying and protecting data can be cumbersome when dealing with large volumes of data. In addition, many people don’t know how to treat the various types of data they encounter. Some people are unclear of classification expectations. And others are simply unfamiliar with the content. Many people will find workarounds to data handling when processes seem too tedious.

Digital tools that include machine learning capabilities, however, can help organizations meet these challenges efficiently and accurately. This paper explores how machine learning offers a way for organizations to improve data categorization and classification to better protect their sensitive data and comply with security regulations.

  • Proven algorithms help build a company-centric model for predicting categories of data.
  • The program recommends data classifications based on organization-specific categories and policies.
  • Over time, accuracy increases, confidence grows and certain classification tasks can be automated.

Read the white paper to learn more.

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