Data Loss Prevention

Machine Learning False Positives

How inaccurate is machine learning? Machine Learning is Very inaccurate The accuracy of machine learning models can vary depending on various factors such as the quality and quantity of training data, the complexity of the problem being solved, the algorithm … Read More

The Achilles Heel of Data Protection

What is the Achilles Heel of DLP & Data Discovery Solutions? Answer: The detection accuracy A virtual zero false positive rate is found to be key to the success of Data Loss Prevention (DLP) systems for several reasons: Data protection: DLP … Read More

Is Sharing Sensitive Data with ChatGPT Risky?

Is Sharing Sensitive Data with ChatGPT Risky? The answer is Yes. Sharing sensitive data with ChatGPT or any other online service carries some inherent risks, and it’s important to be cautious. Good News, GTB’s Data Security that Workstm does cover … Read More

How to Leverage a Cloud Native Data Loss Prevention Platform

How to leverage a Cloud-Native DLP that Workstm Solution A cloud-native Data Loss Prevention (DLP) solution can be a powerful tool to protect sensitive data in modern cloud environments. Here are some steps you can take to leverage a cloud-native … Read More

How does Accurate Sensitive Data Detection Improve Data Governance

Data Governance & Accurate Detection Accurate sensitive data detection plays a critical role in improving data governance. Data governance refers to the overall management of data assets within an organization, including their security, privacy, availability, and usability. Sensitive data, such … Read More

How to Choose the Right Data Loss Prevention Architecture

Data loss prevention (DLP) is an essential aspect of modern cybersecurity. As companies generate and process more data than ever before, the risks of data breaches, leaks, and thefts are higher than ever. Data loss prevention architecture is the foundation … Read More

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