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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 …
Privacy-Preserving Assessment Of Location Data Trustworthiness, Chenyun Dai, Fang-Yu Rao, Gabriel Ghinita, Elisa Bertino
Privacy-Preserving Assessment Of Location Data Trustworthiness, Chenyun Dai, Fang-Yu Rao, Gabriel Ghinita, Elisa Bertino
Cyber Center Publications
Assessing the trustworthiness of location data corresponding to individuals is essential in several applications, such as forensic science and epidemic control. To obtain accurate and trustworthy location data, analysts must often gather and correlate information from several independent sources, e.g., physical observation, witness testimony, surveillance footage, etc. However, such information may be fraudulent, its accuracy may be low, and its vol-
ume may be insufficient to ensure highly trustworthy data. On the other hand, recent advancements in mobile computing and positioning systems, e.g., GPS-enabled cell phones, highway sensors, etc., bring new and effective technological means to track the location of …
Prox-Rbac: A Proximity-Based Spatially Aware Rbac, Michael Kirkpatrick, Maria Luisa Damiani, Elisa Bertino
Prox-Rbac: A Proximity-Based Spatially Aware Rbac, Michael Kirkpatrick, Maria Luisa Damiani, Elisa Bertino
Cyber Center Publications
As mobile computing devices are becoming increasingly dominant in enterprise and government organizations, the need for fine-grained access control in these environments continues to grow. Specifically, advanced forms of access control can be deployed to ensure authorized users can access sensitive resources only when in trusted locations. One technique that has been proposed is to augment role-based access control (RBAC) with spatial constraints. In such a system, an authorized user must be in a designated location in order to exercise the privileges associated with a role. In this work, we extend spatially aware RBAC systems by defining the notion of …
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.