Collecting and analyzing massive data generated from smart devices have become
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …

With the advent of the era of big data, privacy issues have been becoming a hot topic in
public. Local differential privacy (LDP) is a state‐of‐the‐art privacy preservation technique …

Organizations with a large user base, such as Samsung and Google, can potentially benefit
from collecting and mining users' data. However, doing so raises privacy concerns, and risks …

Local differential privacy (LDP) is a recently proposed privacy standard for collecting and
analyzing data, which has been used, eg, in the Chrome browser, iOS and macOS. In LDP …

Local differential privacy (LDP), where users randomly perturb their inputs to provide
plausible deniability of their data without the need for a trusted party, has been adopted …

High-dimensional crowdsourced data collected from numerous users produces rich
knowledge about our society; however, it also brings unprecedented privacy threats to the …

With the rapid development of low-cost consumer electronics and pervasive adoption of next
generation wireless communication technologies, a tremendous amount of data has been …

Local Differential Privacy (LDP) provides provable privacy protection for data collection
without the assumption of the trusted data server. In the real-world scenario, different data …

Big data, which is being explosively generated in various areas, is considered as a new
growth engine for diverse industries. In recent years, analysis of big data has attracted …

In the past decade analysis of big data has proven to be extremely valuable in many
contexts. Local Differential Privacy (LDP) is a state-of-the-art approach which allows …