Our team held its annual in-person meeting, this year on the edge of the Green on the beautiful campus of Dartmouth College. Two days of enriching technical talks about work in progress, brainstorming sessions about upcoming programs, and valued feedback from our NSF program officers… plus opportunities for our five-university group to build connections and collaborative bonds. A few hardy souls hiked to the top of nearby Mount Cardigan the morning after the meeting, in a stiff breeze that reminded us all Fall is approaching.
Jenna Wiens is an Assistant Professor in EECS at the University of Michigan. In the fall of 2014, she joined the CSE division after completing her PhD at MIT.
Professor Wiens primary research interests lie at the intersection of machine learning and medicine. She especially enjoys solving the technical challenges that arise when considering the practical application of machine learning in clinical settings. Currently, she is focused on developing accurate patient risk stratification approaches that leverage data across time and space, with the ultimate goal of reducing the rate of healthcare-associated infections among patients admitted to hospitals in the US.
Anthony Louie recently completed his senior thesis, Information Leakage in Mobile Health Sensors and Applications. Here is the abstract from his thesis:
Mobile health sensors and applications are at risk to information leakage due to the vulnerabilities present on mobile platforms and the risks of using wireless sensors. A possible vulnerability that has not been adequately researched in this area however is data leakage related specifically to how the sensor and the mobile device are designed interact with each other. Such vulnerabilities may exist because of how the health sensors are implemented through the operating system and how hardware is used in the devices. Through an analysis of a mobile health sensor we provide an idea of the current state of mobile health sensor security.
A copy of Louie’s thesis can be found here – Anthony-Louie-Final-Information Leakage in Mobile Health Sensors and Applications
Dongjing He recently submitted her thesis, Security Threats to Android Apps, for her MS degree at the University of Illinois at Urbana-Champaign. He’s research addressed two security vulnerabilities with mobile applications: deficiencies in mobile app development and design ambiguities of the Android operating system. Specifically, He used a three stage study of mHealth apps to investigate potential breach opportunities arising from the reliance on unsecured Internet communications and third party servers. He also researched and discovered side-channel leaks on Android devices. He proposes defense strategies for both vulnerabilities.
Coverage of He’s work can be found in these two articles:
Avi Rubin was recently interviewed by Marcus J. Ranum on the issues surrounding healthcare IT security. The interview appeared on TechTarget.
Avi offers answers to some of the most perplexing issues surrounding healthcare IT security:
- What makes healthcare IT different from other areas of IT security?
- What are some of the major challenges facing the delivery of a secure healthcare IT infrastructure?
- Why are health care professional resistant to attempts at securing healthcare IT?
Avi also provides insight into the goals of the THaW project, and the difference between destructive and constructive security research.
The interview is well worth a few minutes of your time.
Carl Gunter’s THaW group has released an article on “Privacy and Security in the Genomic Era”, submitted to ACM Computing Surveys. This article has a lot more information than a mere literature survey, and it may be beneficial for newcomers in this area. For convenience, a preprint is available on arXiv, and the abstract is below.
They also created an online tutorial (with text, images and videos) to learn the basic biology required to understand this (and in general other) genomic privacy papers.
Authors: Muhammad Naveed, Erman Ayday, Ellen W. Clayton, Jacques Fellay, Carl A. Gunter, Jean-Pierre Hubaux, Bradley A. Malin, XiaoFeng Wang
Genome sequencing technology has advanced at a rapid pace and it is now possible to generate highly-detailed genotypes inexpensively. The collection and analysis of such data has the potential to support various applications, including personalized medical services. While the benefits of the genomics revolution are trumpeted by the biomedical community, the increased availability of such data has major implications for personal privacy; notably because the genome has certain essential features, which include (but are not limited to) (i) an association with certain diseases, (ii) identification capability (e.g., forensics), and (iii) revelation of family relationships. Moreover, direct-to-consumer DNA testing increases the likelihood that genome data will be made available in less regulated environments, such as the Internet and for-profit companies. The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy. While the computer scientists have addressed data privacy for various data types, there has been less attention dedicated to genomic data. Thus, the goal of this paper is to provide a systematization of knowledge for the computer science community. In doing so, we address some of the (sometimes erroneous) beliefs of this field and we report on a survey we conducted about genome data privacy with biomedical specialists. Then, after characterizing the genome privacy problem, we review the state-of-the-art regarding privacy attacks on genomic data and strategies for mitigating such attacks, as well as contextualizing these attacks from the perspective of medicine and public policy. This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward.
We’re pleased to announce a new THaW paper, to appear in the Workshop on the Economics of Information Security (WEIS), June 23-24, to be held at Penn State.
Juhee Kwon and M. Eric Johnson. Meaningful Healthcare Security: Does “Meaningful-Use” Attestation Improve Information Security Performance?
Voluntary mechanisms are often employed to signal performance of difficult-to-observe management practices. In the healthcare sector, financial incentives linked to “meaningful-use” attestation have been a key policy initiative of the Obama administration to accelerate electronic health record (EHR) system adoption while also focusing providers on protecting sensitive healthcare data. As one of the core requirements, meaningful-use attestation requires healthcare providers to attest to having implemented security mechanisms for assessing the potential risks and vulnerabilities to their data. In this paper, we examine whether meaningful-use attestation is achieving its security objective. Using a propensity score matching technique, we analyze a matched sample of 925 U.S. hospitals. We find that external breaches motivate hospitals to pursue meaningful use and that achieving meaningful use does indeed reduce such breaches. We also find that hospitals that achieve meaningful use observe short-term increases in accidental breaches, but see longer-term reductions. These results have implications for managers and policy makers as well as researchers interested in organizational theory and quality management.
We’ll post the paper itself after the workshop.
We are pleased to share an upcoming THaW paper to appear next month at IEEE Workshop on Data Usage Management, a workshop colocated with the IEEE Symposium on Security & Privacy in May 2014.
Abstract: Our genome determines our appearance, gender, diseases, reaction to drugs, and much more. It not only contains information about us but also about our relatives, past generations, and future generations. This creates many policy and technology challenges to protect privacy and manage usage of genomic data. In this paper, we identify various features of genomic data that make its usage management very challenging and different from other types of data. We also describe some ideas about potential solutions and propose some recommendations for the usage of genomic data. [pdf]
The THaW team is pleased to announce the third of its three papers to be presented at the IEEE Symposium on Security & Privacy (aka ‘Oakland’) in May.
ZEBRA: Zero-Effort Bilateral Recurring Authentication
Shrirang Mare, Andrés Molina-Markham, Cory Cornelius, Ronald Peterson, and David Kotz
Abstract: 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. Users often do not log out, however, which is a security risk. The most common solution, inactivity timeouts, inevitably fail security (too long a timeout) or usability (too short a timeout) goals. One solution is to authenticate users continuously while they are using the terminal and automatically log them out when they leave. Several solutions are based on user proximity, but these are not sufficient: they only confirm whether the user is nearby but not whether the user is actually using the terminal. Proposed solutions based on behavioral biometric authentication (e.g., keystroke dynamics) may not be reliable, as a recent study suggests.
To address this problem we propose ZEBRA. In ZEBRA, 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. In our experiments ZEBRA performed continuous authentication with 85% accuracy in verifying the correct user and identified all adversaries within 11 s. For a different threshold that trades security for usability, ZEBRA correctly verified 90% of users and identified all adversaries within 50 s.