"Pacific Northwest National Laboratory and The University of Texas at El Paso Collaborate to Strengthen Data Protection"
Researchers are collaborating to enhance the privacy and security of sensitive data that may include Personally Identifiable Information {PII). Tony Chiang, Data Scientist at Pacific Northwest National Laboratory (PNNL), and Amy Wagler, Professor of Mathematical and Computational Sciences at the University of Texas at El Paso (UTEP), are leading the project. Data privacy and sharing remain a persistent challenge in today's technologically advanced world. The PNNL and UTEP project team wants to protect data from security breaches by creating a Generative Adversarial Network (GAN), or Machine Learning (ML) model, in which two neural networks compete using deep learning techniques to make more accurate predictions. The GAN will use synthetic data instead of real data. The model's discriminators will be incapable of distinguishing between the two data sets, making it impossible to identify and differentiate sensitive data from synthetic data, which is crucial in industries that deal with sensitive data, such as healthcare. This article continues to discuss the PNNL and UTEP project aimed at strengthening the protection of sensitive data.