Cory Cornelius

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Personal mobile devices are increasingly equipped with the capability to sense the physical world (through cameras, microphones, and accelerometers, for example) and the, network world (with Wi-Fi and Bluetooth interfaces). Such devices offer many new opportunities for cooperative sensing applications. For example, users' mobile phones may contribute data(More)
We describe AnonySense, a privacy-aware system for realizing pervasive applications based on collaborative, opportunistic sensing by personal mobile devices. AnonySense allows applications to submit sensing tasks to be distributed across participating mobile devices, later receiving verified, yet anonymized, sensor data reports back from the field, thus(More)
We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on mobile phones. Darwin advances mobile phone sensing through the deployment of efficient but sophisticated machine learning techniques specifically designed to run directly on(More)
Opportunistic sensing allows applications to “task” mobile devices to measure context in a target region. For example, one could leverage sensorequipped vehicles to measure traffic or pollution levels on a particular street, or users’ mobile phones to locate (Bluetooth-enabled) objects in their neighborhood. In most proposed applications, context reports(More)
Anonymizing networks such as Tor allow users to access Internet services privately by using a series of routers to hide the client's IP address from the server. The success of such networks, however, has been limited by users employing this anonymity for abusive purposes such as defacing popular Web sites. Web site administrators routinely rely on(More)
Mobile technology has significant potential to help revolutionize personal wellness and the delivery of healthcare. Mobile phones, wearable sensors, and home-based tele-medicine devices can help caregivers and individuals themselves better monitor and manage their health. While the potential benefits of this "mHealth" technology include better health, more(More)
We propose a simple active method for discovering facts about the chipset, the firmware or the driver of an 802.11 wireless device by observing its responses (or lack thereof) to a series of crafted non-standard or malformed 802.11 frames. We demonstrate that such responses can differ significantly enough to distinguish between a number of popular chipsets(More)
Common authentication methods based on passwords, tokens, or fingerprints perform one-time authentication and rely on users to log out from the computer terminal when they leave. Users often do not log out, however, which is a security risk. The most common solution, inactivity timeouts, inevitably fail security (too long a timeout) or usability (too short(More)
As personal health sensors become ubiquitous, we also expect them to become interoperable. That is, instead of closed, end-to-end personal health sensing systems, we envision standardized sensors wirelessly communicating their data to a device many people already carry today, the cellphone. In an open personal health sensing system, users will be able to(More)
Body-area networks of pervasive wearable devices are increasingly used for health monitoring, personal assistance, entertainment, and home automation. In an ideal world, a user would simply wear their desired set of devices with no configuration necessary: the devices would discover each other, recognize that they are on the same person, construct a secure(More)