Human mobility data in the COVID-19 pandemic: characteristics, applications, and challenges
The COVID-19 pandemic poses unprecedented challenges around the world. Many studies
have applied mobility data to explore spatiotemporal trends over time, investigate …
have applied mobility data to explore spatiotemporal trends over time, investigate …
Modern privacy-preserving record linkage techniques: An overview
Record linkage is the challenging task of deciding which records, coming from disparate
data sources, refer to the same entity. Established back in 1946 by Halbert L. Dunn, the area …
data sources, refer to the same entity. Established back in 1946 by Halbert L. Dunn, the area …
Deepmove: Predicting human mobility with attentional recurrent networks
Human mobility prediction is of great importance for a wide spectrum of location-based
applications. However, predicting mobility is not trivial because of three challenges: 1) the …
applications. However, predicting mobility is not trivial because of three challenges: 1) the …
Narrow band internet of things
In this paper, we review the background and state-of-the-art of the narrow-band Internet of
Things (NB-IoT). We first introduce NB-IoT general background, development history, and …
Things (NB-IoT). We first introduce NB-IoT general background, development history, and …
Knock knock, who's there? Membership inference on aggregate location data
Aggregate location data is often used to support smart services and applications, eg,
generating live traffic maps or predicting visits to businesses. In this paper, we present the …
generating live traffic maps or predicting visits to businesses. In this paper, we present the …
Machine learning in the Internet of Things: Designed techniques for smart cities
Abstract Machine learning is one of the emerging technologies that has grabbed the
attention of academicians and industrialists, and is expected to evolve in the near future …
attention of academicians and industrialists, and is expected to evolve in the near future …
Privacy in trajectory micro-data publishing: a survey
We survey the literature on the privacy of trajectory micro-data, ie, spatiotemporal
information about the mobility of individuals, whose collection is becoming increasingly …
information about the mobility of individuals, whose collection is becoming increasingly …
LSTM-TrajGAN: A deep learning approach to trajectory privacy protection
The prevalence of location-based services contributes to the explosive growth of individual-
level trajectory data and raises public concerns about privacy issues. In this research, we …
level trajectory data and raises public concerns about privacy issues. In this research, we …
SPHA: Smart personal health advisor based on deep analytics
According to a report by the World Health Organization, diseases caused by an unhealthy
lifestyle represent the leading cause of death all over the world. Therefore, it is crucial to …
lifestyle represent the leading cause of death all over the world. Therefore, it is crucial to …
Protecting Trajectory From Semantic Attack Considering -Anonymity, -Diversity, and -Closeness
Nowadays, human trajectories are widely collected and utilized for scientific research and
business purpose. However, publishing trajectory data without proper handling might cause …
business purpose. However, publishing trajectory data without proper handling might cause …