Many modern databases include personal and sensitive correlated data, such as private
information on users connected together in a social network, and measurements of physical …

In the era of information technology and big data, the extraction, commodification, and
control of personal information is redefining how people relate and interact. However, the …

Smart electricity meters have been replacing conventional meters worldwide, enabling
automated collection of fine-grained (eg, every 15 minutes or hourly) consumption data. A …

We propose a versatile privacy framework for quantum systems, termed quantum pufferfish
privacy (QPP). Inspired by classical pufferfish privacy, our formulation generalizes and …

Cross correlations are ubiquitous in time-series IoT data sets such as trajectories from
smartphones and smart meters data in smart grids. Conventional privacy methods have …

Monitoring web browsing behavior can benefit for many data mining tasks, such as top-k
mining and suspicious behavior watching. However, directly releasing private browsing data …

Identifying water end-uses from household meter readings yields valuable commercial and
environmental insights for both customers and water providers. However, smart water meter …

Today, continuous publishing of differentially private query results is the de-facto standard.
However, even today's most advanced privacy frameworks for streams are not customizable …

Many modern machine learning applications involve sensitive correlated data, such as
private information on users connected together in a social network, and measurements of …

Data eye margin test used in conjunction with loopback configuration has become a popular
design for test (DFT) based test method for high speed links. This paper summarizes the …