"New Method Enables Automated Protections for Sensitive Data"

A team of Penn State researchers and graduate students proposed a privacy-preserving data mining framework focussed on protecting the privacy of manufacturing enterprises' sensitive data. According to researchers, cyberattacks against manufacturing companies are growing, and the systems used by these companies are considered essential for economic growth. Therefore, we must increase efforts towards improving the privacy protection of sensitive information in manufacturing. The proposed framework follows the differential privacy approach in which data is mixed with random noise. This article continues to discuss the need to protect manufacturing companies' corporate data and the data mining framework proposed by researchers to preserve the privacy of this data. 

Penn State reports "New Method Enables Automated Protections for Sensitive Data"