This tutorial reviews fundamental contributions to information security. An integrative
viewpoint is taken that explains the security metrics, including secrecy, privacy, and others …

The collection of digital information by governments, corporations, and individuals has
created tremendous opportunities for knowledge-and information-based decision making …

We study the problem of finding low-cost {\em fair clusterings} in data where each data point
may belong to many protected groups. Our work significantly generalizes the seminal work …

Federated learning is generally used in tasks where labels are readily available (eg, next
word prediction). Relaxing this constraint requires design of unsupervised learning …

In data summarization we want to choose $ k $ prototypes in order to summarize a data set.
We study a setting where the data set comprises several demographic groups and we are …

In recent years, privacy-preserving data mining has been studied extensively, because of
the wide proliferation of sensitive information on the internet. A number of algorithmic …

One goal of statistical privacy research is to construct a data release mechanism that
protects individual privacy while preserving information content. An example is a random …

Preserving individual privacy when publishing data is a problem that is receiving increasing
attention. According to the fc-anonymity principle, each release of data must be such that …

The previous literature of privacy preserving data publication has focused on performing"
one-time" releases. Specifically, none of the existing solutions supports re-publication of the …

Trajectory datasets are becoming more and more popular due to the massive usage of GPS
and other location-based devices and services. In this paper, we address privacy issues …