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 …

Federated learning (FL), as a type of distributed machine learning, is capable of significantly
preserving clients' private data from being exposed to adversaries. Nevertheless, private …

With the rise of cloud service providers and the continuous virtualization of data centers,
data center networks are also developing rapidly. As data centers become more and more …

Abstract Internet of Vehicles (IoV) generates large amounts of data at the network edge.
Machine learning models are often built on these data, to enable the detection …

Wireless power transfer (WPT) has offered a revolutionized solution to overcome the driving
range anxieties for electric vehicles (EVs) on remote highways by wirelessly delivering …

In order to overcome the low efficiency of traditional data mining algorithms without
considering weighted association rules, this paper proposes a distributed data flow mining …

차분 프라이버시는 데이터 프라이버시를 보존함과 동시에 데이터를 수집 및 분석할 수 있는
기법으로써 프라이버시 보존형 데이터 활용 분야에서 널리 적용되고 있다. 이러한 차분 …

Differential privacy, which used to collect and analysis data and preserve data privacy, has
been applied widely in data privacy preserving data application. Local differential privacy …