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Full-Text Articles in Physical Sciences and Mathematics
Adapt-Lite: Privacy-Aware, Secure, And Efficient Mhealth Sensing, Shrirang Mare, Jacob Sorber, Minho Shin, Cory Cornelius, David Kotz
Adapt-Lite: Privacy-Aware, Secure, And Efficient Mhealth Sensing, Shrirang Mare, Jacob Sorber, Minho Shin, Cory Cornelius, David Kotz
Dartmouth Scholarship
As healthcare in many countries faces an aging population and rising costs, mobile sensing technologies promise a new opportunity. Using mobile health (mHealth) sensing, which uses medical sensors to collect data about the patients, and mobile phones to act as a gateway between sensors and electronic health record systems, caregivers can continuously monitor the patients and deliver better care. Although some work on mHealth sensing has addressed security, achieving strong security and privacy for low-power sensors remains a challenge. \par We make three contributions. First, we propose Adapt-lite, a set of two techniques that can be applied to existing wireless …
Recognizing Whether Sensors Are On The Same Body, Cory Cornelius, David Kotz
Recognizing Whether Sensors Are On The Same Body, Cory Cornelius, David Kotz
Dartmouth Scholarship
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 seamlessly pair off-the-shelf sensors with their cellphone and expect the system to ıt just work. However, this ubiquity of sensors creates the potential for users to accidentally wear sensors that are not necessarily paired with their own cellphone. A husband, for example, might mistakenly wear a heart-rate …
Anonysense: A System For Anonymous Opportunistic Sensing, Minho Shin, Cory Cornelius, Dan Peebles, Apu Kapadia, David Kotz, Nikos Triandopoulos
Anonysense: A System For Anonymous Opportunistic Sensing, Minho Shin, Cory Cornelius, Dan Peebles, Apu Kapadia, David Kotz, Nikos Triandopoulos
Dartmouth Scholarship
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 \emphtasks\/ to be distributed across participating mobile devices, later receiving verified, yet anonymized, sensor data \emphreports\/ back from the field, thus providing the first secure implementation of this participatory sensing model. We describe our security goals, threat model, and the architecture and protocols of AnonySense. We also describe how AnonySense can support extended security features that can be useful for different applications. We evaluate the security and feasibility of AnonySense through security analysis and prototype …
A Threat Taxonomy For Mhealth Privacy, David Kotz
A Threat Taxonomy For Mhealth Privacy, David Kotz
Dartmouth Scholarship
Networked mobile devices have great potential to enable individuals (and their physicians) to better monitor their health and to manage medical conditions. In this paper, we examine the privacy-related threats to these so-called \emphmHealth\/ technologies. We develop a taxonomy of the privacy-related threats, and discuss some of the technologies that could support privacy-sensitive mHealth systems. We conclude with a brief summary of research challenges.