Seven years ago, the National Science Foundation’s Secure and Trustworthy Cyberspace program awarded a grant creating the Trustworthy Health and Wellness (THaW) project. Most project activities have now wound down, after publishing more than a hundred journal papers, conference papers, workshop contributions, dissertations, theses, patents, and more. We just released an annotated bibliography, with all the references organized in a Zotero library that provides ready access to citation materials and abstracts. In the annotated bibliography we organize papers by cluster (category), identify content tags, and give a brief annotation summarizing the work’s contribution. Thanks to Carl Landwehr for leading this important summary of THaW work!
Connectivity reached new extremes, when wearable technologies enabled smart device communications to appear where analogue watches, rings, and vision-enhancing glasses used to sit. Risks of sensitive data being wrongly transmitted, as a result of malicious or non-malicious intent, grow alongside these new technologies. To ensure that this continued interconnectivity of smart devices and wearables is safe and secure, the THaW team devised, published, and patented LightTouch. This technology, conceptually compatible with existing smart bracelet and display designs, uses optical sensors on the smart device and digital radio links to create a shared secret key that enables the secure and private connection between devices.
LightTouch makes it easy for a person to securely connect their wearable device to a computerized device they encounter, for the purpose of viewing information from their device and possibly sharing that information with nearby acquaintances. To learn more, check out this recent Spotlight in IEEE Computer, or click the links below to read the journal article, the patent specifics, or the conference presentation.
Xiaohui Liang, Ronald Peterson, and David Kotz. Securely Connecting Wearables to Ambient Displays with User Intent. IEEE Transactions on Dependable and Secure Computing 17(4), pages 676–690, July 2020. IEEE. DOI: 10.1109/TDSC.2018.2840979
Xiaohui Liang, Tianlong Yun, Ron Peterson, and David Kotz. Secure System For Coupling Wearable Devices To Computerized Devices with Displays, March 2020. USPTO; U.S. Patent 10,581,606; USPTO. Download from https://patents.google.com/patent/US20170279612A1/en — Priority date 2014-08-18, Grant date 2020-03-03.
Xiaohui Liang, Tianlong Yun, Ronald Peterson, and David Kotz. LightTouch: Securely Connecting Wearables to Ambient Displays with User Intent. In IEEE International Conference on Computer Communications (INFOCOM), May 2017. IEEE. DOI: 10.1109/INFOCOM.2017.8057210
Recent THaW paper:
Future homes are an IoT hotspot that will be particularly at risk. Sensitive information such as passwords, identification, and financial transactions are abundant in the home—as are sensor systems such as digital assistants, smartphones, and interactive home appliances that may unintentionally capture this sensitive information. For example, how motion sensors can capture nearby sounds, including words and keystrokes. We call this oversensing: where authorized access to sensor data provides an application with superfluous and potentially sensitive information. Manufacturers and system designers must employ the principle of least privilege at a more fine-grained level and with awareness of how often different sensors overlap in the sensitive information they leak. We project that directing technical efforts toward a more holistic conception of sensor data in system design and permissioning will reduce risks of oversensing.
Connor Bolton, Kevin Fu, Josiah Hester, and Jun Han. How to curtail oversensing in the home. Communications of the ACM 63(6), pages 20–24, June 2020. ACM. DOI: 10.1145/3396261
The THaW team is pleased to announce one new patent derived from THaW research. For the complete list of patents, visit our Tech Transfer page.
Abstract: Systems and methods are disclosed for providing a trusted computing environment that provides data security in commodity computing systems. Such systems and methods deploy a flexible architecture comprised of distributed trusted platform modules (TPMs) configured to establish a root-of-trust within a heterogeneous network environment comprised of non-TPM enabled IoT devices and legacy computing devices. A data traffic module is positioned between a local area network and one or more non-TPM enabled IoT devices and legacy computing devices, and is configured to control and monitor data communication among such IoT devices and legacy computing devices and from such IoT devices and legacy computing devices to external computers. The data traffic module supports attestation of the IoT devices and legacy computing devices, supports secure boot operations of the IoT devices and legacy computing devices, and provides tamper resistance to such IoT devices and legacy computing devices.
Kevin Kornegay and Willie Lee Thompson II. Decentralized Root-of-Trust Framework for Heterogeneous Networks, November 2020. Morgan State University; USPTO. Download from https://patents.google.com/patent/US20180196945A1/en
A recent THaW paper was nominated for Best Paper at the IoT conference:
With the rapid growth in the number of Internet of Things (IoT) devices with wireless communication capabilities, and sensitive information collection capabilities, it is becoming increasingly necessary to ensure that these devices communicate securely with only authorized devices. A major requirement of this secure communication is to ensure that both the devices share a secret, which can be used for secure pairing and encrypted communication. Manually imparting this secret to these devices becomes an unnecessary overhead, especially when the device interaction is transient. In this work, we empirically investigate the possibility of using an out-of-band communication channel – vibration, generated by a custom smartRing – to share a secret with a compatible IoT device. Through a user study with 12 participants we show that in the best case we can exchange 85.9% messages successfully. Our technique demonstrates the possibility of sharing messages accurately, quickly, and securely as compared to several existing techniques.
To learn more, check out the video presentation here.
Sougata Sen and David Kotz. VibeRing: Using vibrations from a smart ring as an out-of-band channel for sharing secret keys. In Proceedings of the International Conference on the Internet of Things (IoT), page Article#13 (8 pages), October 2020. ACM. DOI: 10.1145/3341162.3343818
A PhD dissertation from a recent ThaW graduate.
The recent popularization of mobile devices equipped with high-performance sensors has given rise to the fast development of mobile sensing technology. Mobile sensing applications, such as gesture recognition, vital sign monitoring, localization, and identification analyze the signals generated by human activities and environment changes, and thus get a better understanding of the environment and human behaviors. While benefiting people’s lives, the growing capability of Mobile Sensing would also spawn new threats to security and privacy. On one hand, while the commercialization of new mobile devices enlarges the design space, it is challenging to design effective mobile sensing systems, which use fewer or cheaper sensors and achieve better performance or more functionalities. On the other hand, attackers can utilize the sensing strategies to track victims’ activities and cause privacy leakages. Mobile sensing attacks usually use side channels and target the information hidden in non-textual data. I present the Mobile Sensing Application-Attack (MSAA) framework, a general model showing the structures of mobile sensing applications and attacks, and how the two faces — the benefits and threats — are connected. MSAA reflects our principles of designing effective mobile sensing systems and exploring information leakages. Our experiment results show that our applications can achieve satisfactory performance, and also confirm the threats of privacy leakage if they are maliciously used, which reveals the two faces of mobile sensing.
Tuo Yu. Two faces of Mobile Sensing, PhD thesis, May 2020. University of Illinois at Urbana-Champaign. Download from http://hdl.handle.net/2142/107938
Recent THaW paper:
When filling out privacy-related forms in public places such as hospitals or clinics, people usually are not aware that the sound of their handwriting can leak personal information. In this paper, we explore the possibility of eavesdropping on handwriting via nearby mobile devices based on audio signal processing and machine learning. By presenting a proof-of-concept system, WritingHacker, we show the usage of mobile devices to collect the sound of victims’ handwriting, and to extract handwriting-specific features for machine learning based analysis. An attacker can keep a mobile device, such as a common smartphone, touching the desk used by the victim to record the audio signals of handwriting. Then, the system can provide a word-level estimate for the content of the handwriting. Moreover, if the relative position between the device and the handwriting is known, a hand motion tracking method can be further applied to enhance the system’s performance. Our prototype system’s experimental results show that the accuracy of word recognition reaches around 70 – 80 percent under certain conditions, which reveals the danger of privacy leakage through the sound of handwriting.
July 2020: Tuo Yu, Haiming Jin, and Klara Nahrstedt. Mobile devices based eavesdropping of handwriting. IEEE Transactions on Mobile Computing 19(7), pages 1649–1663, July 2020. IEEE. DOI: 10.1109/TMC.2019.2912747
Recent THaW paper:
May 2020: Chen Yan, Hocheol Shin, Connor Bolton, Wenyuan Xu, Yongdae Kim, and Kevin Fu. SoK: A Minimalist Approach to Formalizing Analog Sensor Security. pages 233–248, May 2020. IEEE. DOI: 10.1109/sp40000.2020.00026
Over the last six years, several papers demonstrated how intentional analog interference based on acoustics, RF, lasers, and other physical modalities could induce faults, influence, or even control the output of sensors. Damage to the availability and integrity of sensor output carries significant risks to safety-critical systems that make automated decisions based on trusted sensor measurement. This IEEE S&P conference ‘Systematization of Knowledge’ paper provides a framework for assessing the security of analog sensors without sensor engineers needing to learn significantly new notation. The primary goals of the systematization are (1) to enable more meaningful quantification of risk for the design and evaluation of past and future sensors, (2) to better predict new attack vectors, and (3) to establish defensive design patterns that make sensors more resistant to analog attacks.
A new THaW paper was published at USENIX Security last week. It describes using a laser at a distance of 110 meters to stimulate audio sensors on smart speakers and thereby insert audio commands that are accepted as coming from a legitimate user. Techniques for dealing with this vulnerability are proposed.
Takeshi Sugawara, Benjamin Cyr, Sara Rampazzi, Daniel Genkin, and Kevin Fu. Light Commands: Laser-Based Audio Injection Attacks on Voice-Controllable Systems. In Proceedings of the USENIX Security Symposium (USENIX Security), pages 2631–2648, August 2020. USENIX Association.
Paper and video presentation at https://www.usenix.org/conference/usenixsecurity20/presentation/sugawara
Early THaW research on contact tracing is finding new relevance as groups across the US and around the world scramble to develop privacy-preserving contact-tracing apps. Notable app efforts include DP-3T, PEPP-PT, and SafePaths. All of those efforts focus on privacy-preserving apps for retrospective notification of persons who may have had “contact” with a person later determined to be ill with an infectious disease, where “contact” occurs when spending time in close proximity to the infected person. THaW student Aarathi Prasad went further, devising a system that could also detect “close encounters”, e.g., for those who may have visited a place soon after the infected person left. Some diseases, including perhaps the coronavirus, can linger in the air or on surfaces for hours.
Aarathi Prasad and David Kotz. ENACT: Encounter-based Architecture for Contact Tracing. Proceedings of the ACM Workshop on Physical Analytics (WPA), pages 37–42. ACM Press, June 2017. doi:10.1145/3092305.3092310. ©Copyright ACM.
Abstract: Location-based sharing services allow people to connect with others who are near them, or with whom they shared a past encounter. Suppose it were also possible to connect with people who were at the same location but at a different time – we define this scenario as a close encounter, i.e., an incident of spatial and temporal proximity. By detecting close encounters, a person infected with a contagious disease could alert others to whom they may have spread the virus. We designed a smartphone-based system that allows people infected with a contagious virus to send alerts to other users who may have been exposed to the same virus due to a close encounter. We address three challenges: finding devices in close encounters with minimal changes to existing infrastructure, ensuring authenticity of alerts, and protecting privacy of all users. Finally, we also consider the challenges of a real-world deployment.