Differential Privacy is one of the most promising privacy preserving techniques and recent years have witnessed many progresses and applications in this field. However, how to align both privacy and validity of data remains to be solved.
In this presentation, we will briefly introduce local differential privacy as a powerful privacy preserving technique. Additionally, we would describe some practical implements in industrial circle to analyse current challenges and future directions.
