CryptoNumerics Announces CN-Protect for Data Science Python Library

a Toronto-based enterprise software company, announced the launch of CN-Protect for Data Science which enables data scientists to implement state-of-the-art privacy protection, such as differential privacy, directly into their data science stack while maintaining analytical value.
According to a 2017 Kaggle study, two of the top 10 challenges that data scientists face at work are data inaccessibility and privacy regulations, such as GDPR, HIPAA, and CCPA. Additionally, common privacy protection techniques, such as Data Masking, often decimate the analytical value of the data. CN-Protect for Data Science solves these issues by allowing data scientists to seamlessly privacy-protect data sets that retain their analytical value and can subsequently be used for statistical analysis and machine learning.