An Empirical Analysis of Security and Privacy in Health and Medical Systems

Healthcare reform, regulation, and adoption of technology such as wearables are substantially changing both the quality of care and how we receive it. For example, health and fitness devices contain sensors that collect data, wireless interfaces to transmit data, and cloud infrastructures to aggregate, analyze, and share data. FDA-defined class III devices such as pacemakers will soon share these capabilities. While technological growth in health care is clearly beneficial, it also brings new security and privacy challenges for systems, users, and regulators. We group these concepts under health and medical systems to connect and emphasize their importance to healthcare. Challenges include how to keep user health data private, how to limit and protect access to data, and how to securely store and transmit data while maintaining interoperability with other systems. The most critical challenge unique to healthcare is how to balance security and privacy with safety and utility concerns. Specifically, a life-critical medical device must fail-open (i.e., work regardless) in the event of an active threat or attack. This dissertation examines some of these challenges and introduces new systems that not only improve security and privacy but also enhance workflow and usability. Usability is important in this context because a secure system that inhibits workflow is often improperly used or circumvented. We present this concern and our solution in its respective chapter. Each chapter of this dissertation presents a unique challenge, or unanswered question, and solution based on empirical analysis. We present a survey of related work in embedded health and medical systems. The academic and regulatory communities greatly scrutinize the security and privacy of these devices because of their primary function of providing critical care. What we find is that securing embedded health and medical systems is hard, done incorrectly, and is analogous to non-embedded health and medical systems such as hospital servers, terminals, and personally owned mobile devices. A policy called bring your own device (BYOD) allows the use and integration of mobile devices in the workplace. We perform an analysis of Apple iMessage which both implicates BYOD in healthcare and secure messaging protocols used by health and medical systems. We analyze direct memory access engines, a special-purpose piece of hardware to transfer data into and out of main memory, and show that we can chain together memory transfers to perform arbitrary computation. This result potentially affects all computing systems used for healthcare. We also examine HTML5 web workers as they provide stealthy computation and covert communication. This finding is relevant to web applications such as personal and electronic health record portals. We design and implement two novel and secure health and medical systems. One is a wearable device that addresses the problem of authenticating a user (e.g., physician) to a terminal in a usable way. The other is a light-weight and low-cost wireless device we call Beacon+. This device extends the design of Apple's iBeacon specification with unspoofable, temporal, and authenticated advertisements; of which, enables secure location sensing applications that could improve numerous healthcare processes

Sok: Security and privacy in implantable medical devices and body area networks.

Abstract-Balancing security, privacy, safety, and utility is a necessity in the health care domain, in which implantable medical devices (IMDs) and body area networks (BANs) have made it possible to continuously and automatically manage and treat a number of health conditions. In this work, we survey publications aimed at improving security and privacy in IMDs and health-related BANs, providing clear definitions and a comprehensive overview of the problem space. We analyze common themes, categorize relevant results, and identify trends and directions for future research. We present a visual illustration of this analysis that shows the progression of IMD/BAN research and highlights emerging threats. We identify three broad research categories aimed at ensuring the security and privacy of the telemetry interface, software, and sensor interface layers and discuss challenges researchers face with respect to ensuring reproducibility of results. We find that while the security of the telemetry interface has received much attention in academia, the threat of software exploitation and the sensor interface layer deserve further attention. In addition, we observe that while the use of physiological values as a source of entropy for cryptographic keys holds some promise, a more rigorous assessment of the security and practicality of these schemes is required

Classifying Network Protocol Implementation Versions: An OpenSSL Case Study

A new technique is presented for identifying the implementation version number of software that is used for Internet communications. While many programs may exchange version numbers, oftentimes only a small subset of them send any information at all. Furthermore, they usually do not provide accurate details about which implementation is used. We use machine learning techniques to build a feature database and then apply this to network traffic to try to identify specific implementations on servers. We apply our technique to OpenSSL and report our results.National Science Foundation CT-071614

SoK: Security and Privacy in Implantable Medical Devices and Body Area Networks

Abstract—Balancing security, privacy, safety, and utility is a necessity in the health care domain, in which implantable medical devices (IMDs) and body area networks (BANs) have made it possible to continuously and automatically manage and treat a number of health conditions. In this work, we survey publications aimed at improving security and privacy in IMDs and health-related BANs, providing clear definitions and a comprehensive overview of the problem space. We analyze common themes, categorize relevant results, and iden-tify trends and directions for future research. We present a visual illustration of this analysis that shows the progression of IMD/BAN research and highlights emerging threats. We identify three broad research categories aimed at ensuring the security and privacy of the telemetry interface, software, and sensor interface layers and discuss challenges researchers face with respect to ensuring reproducibility of results. We find that while the security of the telemetry interface has received much attention in academia, the threat of software exploitation and the sensor interface layer deserve further attention. In addition, we observe that while the use of physiological values as a source of entropy for cryptographic keys holds some promise, a more rigorous assessment of the security and practicality of these schemes is required. I