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- Mhealth (5)
- Privacy (5)
- Security (3)
- Mobile computing (2)
- Mobile health (2)
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- Wearable (2)
- 16th century (1)
- 17th century (1)
- 18th century (1)
- 19th century (1)
- 20th century (1)
- Amulet (1)
- Anonymization (1)
- Bibliometrics (1)
- Bioimpedance (1)
- Biological classifier (1)
- Biometric (1)
- Communication complexity (1)
- Corruption (1)
- Cortico-striatal (1)
- Cultural evolution (1)
- Data streams (1)
- Esthetics (1)
- Gap-hamming-distance (1)
- Gaussian noise correlation (1)
- Healthcare (1)
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Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Privacy In Mobile Technology For Personal Healthcare, Sasikanth Avancha, Amit Baxi, David Kotz
Privacy In Mobile Technology For Personal Healthcare, Sasikanth Avancha, Amit Baxi, David Kotz
Dartmouth Scholarship
Information technology can improve the quality, efficiency, and cost of healthcare. In this survey, we examine the privacy requirements of \emphmobile\/ computing technologies that have the potential to transform healthcare. Such \emphmHealth\/ technology enables physicians to remotely monitor patients' health, and enables individuals to manage their own health more easily. Despite these advantages, privacy is essential for any personal monitoring technology. Through an extensive survey of the literature, we develop a conceptual privacy framework for mHealth, itemize the privacy properties needed in mHealth systems, and discuss the technologies that could support privacy-sensitive mHealth systems. We end with a list of …
An Optimal Lower Bound On The Communication Complexity Of Gap-Hamming-Distance, Amit Chakrabarti, Oded Regev
An Optimal Lower Bound On The Communication Complexity Of Gap-Hamming-Distance, Amit Chakrabarti, Oded Regev
Dartmouth Scholarship
We prove an optimal Ω(n) lower bound on the randomized communication complex- ity of the much-studied gap-hamming-distance problem. As a consequence, we obtain essentially optimal multipass space lower bounds in the data stream model for a number of fundamental prob- lems, including the estimation of frequency moments. The gap-hamming-distance problem is a communication problem, wherein Alice and Bob receive n-bit strings x and y, respectively. They are promised that the Hamming distance between x and y is either at least n/2 + √n or at most n, and their goal is to decide which of these is the case. Since …
Understanding Sharing Preferences And Behavior For Mhealth Devices, Aarathi Prasad, Jacob Sorber, Timothy Stablein, Denis Anthony, David Kotz
Understanding Sharing Preferences And Behavior For Mhealth Devices, Aarathi Prasad, Jacob Sorber, Timothy Stablein, Denis Anthony, David Kotz
Dartmouth Scholarship
mHealth devices offer many potential benefits to patients, health providers and others involved in the patients' healthcare. If patients are not in control of the collection and sharing of their personal health information, they will have privacy concerns even while enjoying the benefits of the devices. We investigated patients' willingness to share their personal health information, collected using mHealth devices, with their family, friends, third parties and the public. Our findings are based on a user study conducted with 41 participants. The best way to understand people's privacy concerns is to give them the opportunity to use the device and …
Who Wears Me? Bioimpedance As A Passive Biometric, Cory Cornelius, Jacob Sorber, Ronald Peterson, Joe Skinner, Ryan Halter, David Kotz
Who Wears Me? Bioimpedance As A Passive Biometric, Cory Cornelius, Jacob Sorber, Ronald Peterson, Joe Skinner, Ryan Halter, David Kotz
Dartmouth Scholarship
Mobile and wearable systems for monitoring health are becoming common. If such an mHealth system knows the identity of its wearer, the system can properly label and store data collected by the system. Existing recognition schemes for such mobile applications and pervasive devices are not particularly usable – they require ıt active engagement with the person (e.g., the input of passwords), or they are too easy to fool (e.g., they depend on the presence of a device that is easily stolen or lost). \par We present a wearable sensor to passively recognize people. Our sensor uses the unique electrical properties …
Quantitative Patterns Of Stylistic Influence In The Evolution Of Literature, James M. Hughes, Nicholas J. Foti, David C. Krakauer, Daniel N. Rockmore
Quantitative Patterns Of Stylistic Influence In The Evolution Of Literature, James M. Hughes, Nicholas J. Foti, David C. Krakauer, Daniel N. Rockmore
Dartmouth Scholarship
Literature is a form of expression whose temporal structure, both in content and style, provides a historical record of the evolution of culture. In this work we take on a quantitative analysis of literary style and conduct the first large-scale temporal stylometric study of literature by using the vast holdings in the Project Gutenberg Digital Library corpus. We find temporal stylistic localization among authors through the analysis of the similarity structure in feature vectors derived from content-free word usage, nonhomogeneous decay rates of stylistic influence, and an accelerating rate of decay of influence among modern authors. Within a given time …
Passive Biometrics For Pervasive Wearable Devices (Poster Paper), Cory Cornelius, Zachary Marois, Jacob Sorber, Ron Peterson, Shrirang Mare, David Kotz
Passive Biometrics For Pervasive Wearable Devices (Poster Paper), Cory Cornelius, Zachary Marois, Jacob Sorber, Ron Peterson, Shrirang Mare, David Kotz
Dartmouth Scholarship
Wearable devices – like the FitBit, MOTOACTV, and Jawbone UP – are increasingly becoming more pervasive whether for monitoring health and fitness, personal assistance, or home automation. While pervasive wearable devices have long been researched, we are now beginning to see the fruits of this research in the form of commercial offerings. Today, many of these commercial wearable devices are closed systems that do not interoperate with other devices a person might carry. We believe, however, these commercial offerings signal the coming of wireless body-area networks that will connect these pervasive wearable devices and leverage existing devices a user already …
An Amulet For Trustworthy Wearable Mhealth, Jacob Sorber, Minho Shin, Ronald Peterson, Cory Cornelius, Shrirang Mare, Aarathi Prasad, Zachary Marois, Emma N. Smithayer, David Kotz
An Amulet For Trustworthy Wearable Mhealth, Jacob Sorber, Minho Shin, Ronald Peterson, Cory Cornelius, Shrirang Mare, Aarathi Prasad, Zachary Marois, Emma N. Smithayer, David Kotz
Dartmouth Scholarship
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 effective healthcare, and reduced cost, this technology also poses significant security and privacy challenges. In this paper we propose \emphAmulet, an mHealth architecture that provides strong security and privacy guarantees while remaining easy to use, and outline the research and engineering challenges required to realize the Amulet vision.
Derivation Of A Novel Efficient Supervised Learning Algorithm From Cortical-Subcortical Loops, Ashok Chandrashekar, Richard Granger
Derivation Of A Novel Efficient Supervised Learning Algorithm From Cortical-Subcortical Loops, Ashok Chandrashekar, Richard Granger
Dartmouth Scholarship
Although brain circuits presumably carry out powerful perceptual algorithms, few instances of derived biological methods have been found to compete favorably against algorithms that have been engineered for specific applications. We forward a novel analysis of a subset of functions of cortical-subcortical loops, which constitute more than 80% of the human brain, thus likely underlying a broad range of cognitive functions. We describe a family of operations performed by the derived method, including a non-standard method for supervised classification, which may underlie some forms of cortically dependent associative learning. The novel supervised classifier is compared against widely used algorithms for …
Effects Of Network Trace Sampling Methods On Privacy And Utility Metrics, Phillip A. Fazio, Keren Tan, David Kotz
Effects Of Network Trace Sampling Methods On Privacy And Utility Metrics, Phillip A. Fazio, Keren Tan, David Kotz
Dartmouth Scholarship
Researchers choosing to share wireless-network traces with colleagues must first anonymize sensitive information, trading off the removal of information in the interest of identity protection and the preservation of useful data within the trace. While several metrics exist to quantify this privacy-utility tradeoff, they are often computationally expensive. Computing these metrics using a \emphsample\/ of the trace could potentially save precious time. In this paper, we examine several sampling methods to discover their effects on measurement of the privacy-utility tradeoff when anonymizing network traces. We tested the relative accuracy of several packet and flow-sampling methods on existing privacy and utility …