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 …

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 …

In this paper, we study Local Information Privacy (LIP). As a context-aware privacy notion,
LIP relaxes the de facto standard privacy notion of local differential privacy (LDP) by …

Location estimation of underwater sensor networks (USNs) has become a critical
technology, due to its fundamental role in the sensing, communication and control of ocean …

Motivated by the security risks of deep neural networks, such as various membership and
attribute inference attacks, differential privacy has emerged as a promising approach for …

Federated Learning (FL) is a decentralized learning mechanism that has attracted
increasing attention due to its achievements in computational efficiency and privacy …

Frequent pattern mining is an important class of knowledge discovery problems. It aims at
finding out high-frequency items or structures (eg, itemset, sequence) in a database, and …

In this paper, we tackle the problem of answering multi-dimensional range queries under
local differential privacy. There are three key technical challenges: capturing the correlations …

Estimating frequencies of certain items among a population is a basic step in data analytics,
which enables more advanced data analytics (eg, heavy hitter identification, frequent pattern …