TISH: Trustworthy Information Systems for Healthcare (2009-2018)

This project is no longer active; this page is no longer updated.

Related projects: [Amanuensis], [Amulet], [Auracle], [SIMBA], [THaW]

Related keywords: [authentication], [iot], [mhealth], [patent], [privacy], [security], [sensors], [survey], [wearable], [wifi]


In the TISH (Trustworthy Information Systems for Healthcare) project we explored wearable and portable devices for use in health monitoring and management, with an emphasis on the security and privacy issues that arise with these devices and their apps. We considered wearable, mobile, or home-based technologies being used by patients or clinical staff, and addressed issues of person identification and authentication, privacy and data sharing, secure data processing, anonymity in wireless-network communications, and mobile sensing. Some of this work is summarized below.

Much of this work culminated in the THaW project and inspired work in the Amanuensis, Amulet, Auracle, and SIMBA projects.

This page also includes work funded in the SHARPS and PC3 grants.

Overview, challenges, surveys: Early in this project we wrote an extensive survey of the literature regarding privacy in mHealth technology [avancha:survey], and extracted a threat model from that work [kotz:mhealth-threats, kotz:mhealth-spimacs]. Later in the project we held a workshop to review the state of the science [anthony:sith3].

diagram of the bioimpedance bracelet and its electronics Biometric identification/verification. In this work we address two critical challenges. First, we evaluate the use of bioimpedance for recognizing who is wearing wireless sensors and show that bioimpedance is a feasible biometric. Second, we investigate the use of accelerometers for verifying whether two of these wireless sensors are on the same person and show that our method is successful as distinguishing between sensors on the same body and on different bodies. We stress that any solution to these problems must be usable, meaning the user should not have to do anything but attach the sensor to their body and have them just work. This work is best described in Cornelius' PhD thesis [cornelius:thesis], and also appeared in several papers [cornelius:wearable, cornelius:impedance, cornelius:j-same-body, cornelius:same-body, cornelius:biometrics-poster]. We also conducted an early investigation into the prospect of identifying people with their 'vocal resonance', that is, the sound of their voice as recorded through their body [cornelius:voice-tr]; this work later was finished under the THaW project.

Authentication of computer users: We invented the concept of bilateral authentication and applied it to the challenge of continuous authentication of desktop computer users. 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. One solution is to authenticate users continuously while they are using the terminal and automatically log them out when they leave. In our solution, explored fully in Mare's dissertation [mare:thesis] and the papers below, a user wears a bracelet (with a built-in accelerometer, gyroscope, and radio) on her dominant wrist. When the user interacts with a computer terminal, the bracelet records the wrist movement, processes it, and sends it to the terminal. The terminal compares the wrist movement with the inputs it receives from the user (via keyboard and mouse), and confirms the continued presence of the user only if they correlate. Because the bracelet is on the same hand that provides inputs to the terminal, the accelerometer and gyroscope data and input events received by the terminal should correlate because their source is the same -- the user's hand movement. Our approach performed continuous authentication with 85% accuracy in verifying the correct user and identified all adversaries within 11 seconds. For a different threshold that trades security for usability, it correctly verified 90% of users and identified all adversaries within 50 seconds [mare:thesis, mare:patent9832206, mare:zebra-tr, mare:zebra14]. This project was renamed CSAW and was completed under the THaW project.

Privacy and data sharing: We explored several questions related to the willingness of people to share mHealth data, the means to attest to its provenance, and privacy-preserving systems to retrospectively detect when people were in spatio-temporal proximity. In Prasad's dissertation [prasad:thesis] and related papers we present our findings about factors that affect people's sharing behavior, describe scenarios in which people may wish to collect and share their personal health-related information with others, but may be hesitant to disclose the information if necessary controls are not available to protect their privacy, and propose frameworks to provide the desired privacy controls. We introduce the concept of close encounters that allow users to share data with other people who may have been in spatio-temporal proximity. We developed two smartphone-based systems that leverage stationary sensors and beacons to determine whether users are in spatio-temporal proximity. The first system, ENACT, allows patients diagnosed with a contagious airborne disease to alert others retrospectively about their possible exposure to airborne virus. The second system, SPICE, allows users to collect sensor information, retrospectively, from others with whom they shared a close encounter. We present design and implementation of the two systems, analyse their security and privacy guarantees, and evaluate the systems on various performance metrics. Finally, we evaluate how Bluetooth beacons and Wi-Fi access points can be used in support of these systems for close encounters, and present our experiences and findings from a deployment study on Dartmouth campus. [prasad:thesis, prasad:nethealth13, prasad:provenance-poster, prasad:bfitbit, prasad:fitbit, prasad:msthesis].

Hide-n-Sense: wireless security and anonymity. Although some work on mHealth sensing addressed security, achieving strong privacy for low-power sensors remains a challenge. We make three contributions. First, we propose an mHealth sensing protocol that provides strong security and privacy properties at the link layer, with low energy overhead, suitable for low-power sensors. The protocol uses three novel techniques: adaptive security, to dynamically modify transmission overhead; MAC striping, to make forgery difficult even for small-sized Message Authentication Codes; and asymmetric resource requirements, in recognition of the limited resources in tiny mHealth sensors. Second, we demonstrate its feasibility by implementing a prototype on a Chronos wrist device, and evaluating it experimentally. Third, we provide a security, privacy, and energy analysis of our system [mare:hns-j, mare:hns-w, mare:hns-tr].

Plug-n-Trust: secure sensing and data processing. Plug-n-Trust (PnT) was a novel approach to protecting both the confidentiality and integrity of safety-critical medical sensing and data processing on vulnerable mobile phones. With PnT, a plug-in smart card provides a trusted computing environment, keeping data safe even on a compromised mobile phone. By design, PnT is simple to use and deploy, while providing a flexible programming interface amenable to a wide range of applications. We designed an implementation for Java-based smart cards and Android phones, in which we use a split-computation model with a novel path hashing technique to verify proper behavior without exposing confidential data. Our experimental evaluation demonstrates that PnT achieves its security goals while incurring acceptable overhead [sorber:pnt, sorber:pnt-poster].

Sensing blood-pressure reliably: We built a user-friendly, mobile health-data collection system designed to support minimally trained, non-clinical health workers to gather data about blood pressure and body weight using off-the-shelf medical sensors. This system comprises a blood-pressure cuff, a weighing scale and a portable point-of-sales printer. With this system, we introduced a new method to record contextual information associated with a blood-pressure reading using a tablet's touchscreen and accelerometer. This contextual information can be used to verify that a patient's lower arm remained well-supported and stationary during her blood-pressure measurement. The work resulted in Murthy's MS thesis and Smithayer's BA thesis [murthy:thesis, murthy:bp, smithayer:bp].


Many people were involved in TISH projects; those involved as co-authors include Denise Anthony, Sasikanth Avancha, Amit Baxi, Andrew Campbell, Cory Cornelius, Andrew Gettinger, Carl A. Gunter, Ryan Halter, M. Eric Johnson, Shloka R. Kini, David Kotz, Shrirang Mare, Zachary Marois, Lisa Marsch, Andrés Molina-Markham, Rima Narayana Murthy, Kolin Paul, Ronald Peterson, Aarathi Prasad, Minho Shin, Joseph Skinner, Sean Smith, Emma N. Smithayer, Jacob Sorber, and Timothy Stablein.


TISH research was primarily funded by the NSF Trustworthy Computing program (Award 0910842), but we also had related funding from the NSF IIS program (Award 1016823), from the NSF Computer and Network Systems program (PC3) (Award 1143548), from HHS-ONC through the SHARP program (see SHARPS website), the Department of Homeland Security (DHS-NCSD) through ISTS, and from the Intel University Research Council.

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Papers (tagged 'tish')

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[Kotz research]