Adversarial Perturbation for Privacy Preservation

While adversarial examples (AEs) or adversarial perturbations (APs) are usually treated as a security risk up to date, they can also serve as privacy protection tools when facing deep learning-based privacy attacks. This chapter will first introduce a privacy model for visual data, one of the most important types of data in deep learning applications. Then we will discuss AP-based privacy protection mechanisms that incorporate different levels of privacy. While the research on this topic is still in its infancy stage, this chapter will overview the state-of-the-art works and shed light on future research.