Users' privacy is vulnerable at all stages of the deep learning process. Sensitive information
of users may be disclosed during data collection, during training, or even after releasing the …

Modern cyber physical systems (CPSs) has widely being used in our daily lives because of
development of information and communication technologies (ICT). With the provision of …

Data privacy arises as one of the most important concerns, facing the pervasive
commoditization of big data statistic analysis in Internet of Things (IoT). Current solutions are …

The construction of smart cities will bring about a higher quality of life to the masses through
digital interconnectivity, leading to increased efficiency and accessibility in cities. Smart …

Differential privacy is an essential and prevalent privacy model that has been widely
explored in recent decades. This survey provides a comprehensive and structured overview …

Concerns on location privacy frequently arise with the rapid development of GPS enabled
devices and location-based applications. While spatial transformation techniques such as …

Enabling situation awareness in a given environment thus relies on being able to identify an
appropriate set of perception elements, coupled with higher-level comprehension patterns …

Differential privacy is becoming a gold standard notion of privacy; it offers a guaranteed
bound on loss of privacy due to release of query results, even under worst-case …

The widespread adoption of continuously connected smartphones and tablets developed
the usage of mobile applications, among which many use location to provide geolocated …

The data collected in Internet of Thing (IoT) systems (IoT data) have stimulated dramatic
extension to the boundary of commercialized data statistic analysis, owing to the pervasive …