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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Securing Information Technology In Healthcare, Denise Anthony, Andrew T. Campbell, Thomas Candon, Andrew Gettinger, David Kotz, Lisa A. Marsch, Andrés Molina-Markham, Karen M. Page, Sean W. Smith, Carl A. Gunter, M. Eric Johnson
Securing Information Technology In Healthcare, Denise Anthony, Andrew T. Campbell, Thomas Candon, Andrew Gettinger, David Kotz, Lisa A. Marsch, Andrés Molina-Markham, Karen M. Page, Sean W. Smith, Carl A. Gunter, M. Eric Johnson
Dartmouth Scholarship
Information technology (IT) has great potential to improve healthcare quality while also improving efficiency, and thus has been a major focus of recent healthcare reform efforts. However, developing, deploying and using IT that is both secure and genuinely effective in the complex clinical, organizational and economic environment of healthcare is a significant challenge. Further, it is imperative that we better understand the privacy concerns of patients and providers, as well as the ability of current technologies, policies, and laws to adequately protect privacy. The Securing Information Technology in Healthcare (SITH) workshops were created to provide a forum to discuss security …
Flexiterm: A Flexible Term Recognition Method, Irena Spasić, Mark Greenwood, Alun Preece, Nick Francis, Glyn Elwyn
Flexiterm: A Flexible Term Recognition Method, Irena Spasić, Mark Greenwood, Alun Preece, Nick Francis, Glyn Elwyn
Dartmouth Scholarship
Background: The increasing amount of textual information in biomedicine requires effective term recognition methods to identify textual representations of domain-specific concepts as the first step toward automating its semantic interpretation. The dictionary look-up approaches may not always be suitable for dynamic domains such as biomedicine or the newly emerging types of media such as patient blogs, the main obstacles being the use of non-standardised terminology and high degree of term variation.
Elfbac: Using The Loader Format For Intent-Level Semantics And Fine-Grained Protection, Julian Bangert, Sergey Bratus, Rebecca Shapiro, Michael E. Locasto, Jason Reeves, Sean W. Smith, Anna Shubina
Elfbac: Using The Loader Format For Intent-Level Semantics And Fine-Grained Protection, Julian Bangert, Sergey Bratus, Rebecca Shapiro, Michael E. Locasto, Jason Reeves, Sean W. Smith, Anna Shubina
Computer Science Technical Reports
Adversaries get software to do bad things by rewriting memory and changing control flow. Current approaches to protecting against these attacks leave many exposures; for example, OS-level filesystem protection and OS/architecture support of the userspace/kernelspace distinction fail to protect corrupted userspace code from changing userspace data. In this paper we present a new approach: using the ELF/ABI sections already produced by the standard binary toolchain to define, specify, and enforce fine-grained policy within an application's address space. We experimentally show that enforcement of such policies would stop a large body of current attacks and discuss ways we could extend existing …
Interpreting And Reconstructing Data From Sensor Networks, Jonathan H. Guinther
Interpreting And Reconstructing Data From Sensor Networks, Jonathan H. Guinther
Computer Science Technical Reports
Geophysical phenomena are often three-dimensional, time-variant, and physically large, making them difficult to measure. As wireless sensor nodes become cheaper, smaller, and more powerful, using a sensor swarm as a sampling framework seems to be a viable approach to this problem. However, samples from the network can be sparse and unstructured, creating an incomplete picture. Thus, the question addressed by this project is the following: How can we easily construct and interpret the best model of the underlying reality over some domain, given a possibly sparse and irregular set of samples? We present the design, implementation, and evaluation of the …
Mexsvms: Mid-Level Features For Scalable Action Recognition, Du Tran, Lorenzo Torresani
Mexsvms: Mid-Level Features For Scalable Action Recognition, Du Tran, Lorenzo Torresani
Computer Science Technical Reports
This paper introduces MEXSVMs, a mid-level representation enabling efficient recognition of actions in videos. The entries in our descriptor are the outputs of several movement classifiers evaluated over spatial-temporal volumes of the image sequence, using space-time interest points as low-level features. Each movement classifier is a simple exemplar-SVM, i.e., an SVM trained using a single positive video and a large number of negative sequences. Our representation offers two main advantages. First, since our mid-level features are learned from individual video exemplars, they require minimal amount of supervision. Second, we show that even simple linear classification models trained on our global …