One of the challenges in implementing data privacy is the requirement to maintain the usefulness (utility) of the privatized data. During the data privacy process, original data suffers loss of statistical value regardless of the strong levels of data privacy, making the usability of the privatized data difficult to use. In addition, finding a balance between privacy and usability requirements is often problematic and necessitates trade-offs. In this workshop, we investigate data privacy and usability preservation using machine learning classification as a gauge.
Dr. Rose Shumba