Related papers: Privacy-preserving classifiers recognize shared mo…
While smartphones and WiFi networks are bringing many positive changes to people's lives, they are susceptible to traffic analysis attacks, which infer user's private information from encrypted traffic. Existing traffic analysis attacks…
Advances in wireless localization techniques aiming to exploit context-dependent data has been leading to a growing interest in services able of localizing or tracking targets inside buildings with high accuracy and precision. Hence, the…
This paper presents an end-to-end deep learning framework using passive WiFi sensing to classify and estimate human respiration activity. A passive radar test-bed is used with two channels where the first channel provides the reference WiFi…
Understanding human behavior is an important task and has applications in many domains such as targeted advertisement, health analytics, security, and entertainment, etc. For this purpose, designing a system for activity recognition (AR) is…
Understanding the mobility of humans and their devices is a fundamental problem in mobile computing. While there has been much work on empirical analysis of human mobility using mobile device data, prior work has largely assumed devices to…
The extensive use of smartphones and wearable devices has facilitated many useful applications. For example, with Global Positioning System (GPS)-equipped smart and wearable devices, many applications can gather, process, and share rich…
Smartphone apps for exposure notification and contact tracing have been shown to be effective in controlling the COVID-19 pandemic. However, Bluetooth Low Energy tokens similar to those broadcast by existing apps can still be picked up far…
Human doing actions will result in WiFi distortion, which is widely explored for action recognition, such as the elderly fallen detection, hand sign language recognition, and keystroke estimation. As our best survey, past work recognizes…
The Internet of Things (IoT) promises to improve user utility by tuning applications to user behavior, but revealing the characteristics of a user's behavior presents a significant privacy risk. Our previous work has established the…
WiFi fingerprint-based indoor localization has been widely studied, but most existing approaches focus on absolute positioning and rely on dense coordinate annotations, which are costly to obtain at scale. In this paper, we study a…
Our work demonstrates a new set of silent reconnaissance attacks, which leverages the presence of commodity WiFi devices to track users inside private homes and offices, without compromising any WiFi network, data packets, or devices. We…
Transportation has become of evermore importance in the last years, affecting people's satisfaction and significantly impacting their quality of life. In this paper we present a low-cost infrastructure to collect passive Wi-Fi probes with…
Mobility and network traffic have been traditionally studied separately. Their interaction is vital for generations of future mobile services and effective caching, but has not been studied in depth with real-world big data. In this paper,…
Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of…
The ability to reliably predict the future quality of a wireless channel, as seen by the media access control layer, is a key enabler to improve performance of future industrial networks that do not rely on wires. Knowing in advance how…
Studies using massive, passively data collected from communication technologies have revealed many ubiquitous aspects of social networks, helping us understand and model social media, information diffusion, and organizational dynamics. More…
A day in the life of a person involves a broad range of activities which are common across many people. Going beyond diurnal cycles, a central question is: to what extent do individuals act according to patterns shared across an entire…
This paper presents MultiTrack, a commodity WiFi-based human sensing system that can track multiple users and recognize the activities of multiple users performing them simultaneously. Such a system can enable easy and large-scale…
This work presents a simulation framework to generate human micro-Dopplers in WiFi based passive radar scenarios, wherein we simulate IEEE 802.11g complaint WiFi transmissions using MATLAB's WLAN toolbox and human animation models derived…
This study evaluates the effectiveness of using Google Maps Location History data to identify joint activities in social networks. To do so, an experiment was conducted where participants were asked to execute daily schedules designed to…