相关论文: Mobile Sensor Data Anonymization

Sensitive inferences and user re-identification are major threats to privacy when raw sensor data from wearable or portable devices are shared with cloud-assisted applications. To mitigate these threats, we propose mechanisms to transform…

The abundance of data collected by sensors in Internet of Things (IoT) devices, and the success of deep neural networks in uncovering hidden patterns in time series data have led to mounting privacy concerns. This is because private and…

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 generated by motion sensors reflect directly the activities…

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 data is critical to the success of many beneficial applications…

This paper proposes a sensor data anonymization model that is trained on decentralized data and strikes a desirable trade-off between data utility and privacy, even in heterogeneous settings where the sensor data have different underlying…

The recent rapid advancements in both sensing and machine learning technologies have given rise to the universal collection and utilization of people's biometrics, such as fingerprints, voices, retina/facial scans, or gait/motion/gestures…

The use of virtual and augmented reality devices is increasing, but these sensor-rich devices pose risks to privacy. The ability to track a user's motion and infer the identity or characteristics of the user poses a privacy risk that has…

Human motion is a behavioral biometric trait that can be used to identify individuals and infer private attributes such as medical conditions. This poses a serious threat to privacy as motion extraction from video and motion capture are…

Object slip perception is essential for mobile manipulation robots to perform manipulation tasks reliably in the dynamic real-world. Traditional approaches to robot arms' slip perception use tactile or vision sensors. However, mobile robots…

Sensors embedded in mobile smart devices can monitor users' activity with high accuracy to provide a variety of services to end-users ranging from precise geolocation, health monitoring, and handwritten word recognition. However, this…

There is a known tension between the need to analyze personal data to drive business and privacy concerns. Many data protection regulations, including the EU General Data Protection Regulation (GDPR) and the California Consumer Protection…

We introduce a novel approach to user authentication called Motion ID. The method employs motion sensing provided by inertial measurement units (IMUs), using it to verify the persons identity via short time series of IMU data captured by…

Smartphones have become quite pervasive in various aspects of our daily lives. They have become important links to a host of important data and applications, which if compromised, can lead to disastrous results. Due to this, today's…

In this article we propose the use of accelerometer embedded by default in smartphone as a cost-effective, reliable and efficient way to provide remote physical activity monitoring for the elderly and people requiring healthcare service.…

Physical activity patterns can be informative about a patient's health status. Traditionally, activity data have been gathered using patient self-report. However, these subjective data can suffer from bias and are difficult to collect over…

Modern smartphones contain motion sensors, such as accelerometers and gyroscopes. These sensors have many useful applications; however, they can also be used to uniquely identify a phone by measuring anomalies in the signals, which are a…

Human activity recognition based on wearable sensor data has been an attractive research topic due to its application in areas such as healthcare and smart environments. In this context, many works have presented remarkable results using…

Human physical motion activity identification has many potential applications in various fields, such as medical diagnosis, military sensing, sports analysis, and human-computer security interaction. With the recent advances in smartphones…

Recently, occluded person re-identification(Re-ID) remains a challenging task that people are frequently obscured by other people or obstacles, especially in a crowd massing situation. In this paper, we propose a self-supervised deep…

Nowadays smartphones come embedded with multiple motion sensors, such as an accelerometer, a gyroscope and an orientation sensor. With these sensors, apps can gather more information and therefore provide end users with more functionality.…