Accelerometer-based activity recognition (AAR) attracted a lot of attentions due to the wide
spread of smartphones with energy-efficiency. However, since accelerometer data contains …

There is growing concern about how personal data are used when users grant applications
direct access to the sensors of their mobile devices. In fact, high resolution temporal data …

Differential privacy (DP) is a method to protect individual privacy when the data is used for
downstream analytical tasks. The core ability of DP to quantity privacy numerically separates …

User privacy is an important concern that should be handled in data intensive applications.
Interestingly, differential privacy is a privacy model that can be applied to such datasets. This …

An increasing number of sensors on mobile, Internet of things (IoT), and wearable devices
generate time-series measurements of physical activities. Though access to the sensory …

Internet of Things (IoT) allow data collection and sharing of many aspects of our daily life.
With the huge amount of data transferred via IoT devices, privacy concerns need to be …

Differential privacy concepts have been successfully used to protect anonymity of individuals
in population-scale analysis. Sharing of mobile sensor data, especially physiological data …

Many services based on human activity recognition (HAR) have been developed; however,
user activity data include a large amount of private information. Although privacy protection …

The convergence of Internet of Things (IoT) and edge computing allows for the collection
and sharing of data from human wearable devices. With the huge amount of data transferred …

The daily activities performed by a disabled or elderly person can be monitored by a smart
environment, and the acquired data can be used to learn a predictive model of user …