A Statistical Overview on Data Privacy

TL;DR

This paper provides a comprehensive overview of statistical methods, challenges, and opportunities in data privacy, emphasizing balancing data utility with individual privacy protection amid growing big data concerns.

Contribution

It offers a broad survey of current statistical approaches and challenges in data privacy, highlighting recent developments and future research directions.

Findings

Overview of statistical privacy techniques

Discussion of current challenges in data privacy

Identification of future opportunities in privacy research

Abstract

The eruption of big data with the increasing collection and processing of vast volumes and variety of data have led to breakthrough discoveries and innovation in science, engineering, medicine, commerce, criminal justice, and national security that would not have been possible in the past. While there are many benefits to the collection and usage of big data, there are also growing concerns among the general public on what personal information is collected and how it is used. In addition to legal policies and regulations, technological tools and statistical strategies also exist to promote and safeguard individual privacy, while releasing and sharing useful population-level information. In this overview, I introduce some of these approaches, as well as the existing challenges and opportunities in statistical data privacy research and applications to better meet the practical needs of privacy protection and information sharing.