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Wireless connectivity is becoming common in increasingly diverse personal devices, enabling various interoperation- and Internet-based applications and services. More and more interconnected devices are simultaneously operated by a single user with short-lived connections, making usable device authentication methods imperative to ensure both high security and seamless user experience. Unfortunately, current authentication methods that heavily require human involvement, in addition to form factor and mobility constraints, make this balance hard to achieve, often forcing users to choose between security and convenience. In this work, we present a novel over-the-air device authentication scheme named AEROKEY that achieves both high security and high usability. With virtually no hardware overhead, AEROKEY leverages ubiquitously observable ambient electromagnetic radiation to autonomously generate spatiotemporally unique secret that can be derived only by devices that are closely located to each other. Devices can make use of this unique secret to form the basis of a symmetric key, making the authentication procedure more practical, secure and usable with no active human involvement. We propose and implement essential techniques to overcome challenges in realizing AEROKEY on low-cost microcontroller units, such as poor time synchronization, lack of precision analog front-end, and inconsistent sampling rates. Our real-world experiments demonstrate reliable authentication as well as its robustness against various realistic adversaries with low equal-error rates of 3.4% or less and usable authentication time of as low as 24 s. 

Autonomous vehicles (AVs) use diverse sensors to understand their surroundings as they continually make safety-critical decisions. However, establishing trust with other AVs is a key prerequisite because safety-critical decisions cannot be made based on data shared from untrusted sources. Existing protocols require an infrastructure network connection and a third-party root of trust to establish a secure channel, which are not always available.In this paper, we propose a sensor-fusion approach for mobile trust establishment, which combines GPS and visual data. The combined data forms evidence that one vehicle is nearby another, which is a strong indication that it is not a remote adversary hence trustworthy. Our preliminary experiments show that our sensor-fusion approach achieves above 80% successful pairing of two legitimate vehicles observing the same object with 5 meters of error. Based on these preliminary results, we anticipate that a refined approach can support fuzzy trust establishment, enabling better collaboration between nearby AVs. 

As we add more autonomous and semi-autonomous vehicles (AVs) to our roads, their effects on passenger and pedestrian safety are becoming more important. Despite extensive testing before deployment, AV systems are not perfect at identifying hazards in the roadway. Although a particular AV’s sensors and software may not be 100% accurate at identifying hazards, there is an untapped pool of information held by other AVs in the vicinity that could be used to quickly and accurately identify roadway hazards before they present a safety threat. 

For error-resilient applications, such as machine learning and signal processing, a significant improvement in energy efficiency can be achieved by relaxing exactness constraint on output quality. This paper presents a taxonomy of hardware techniques to exploit the trade-off between energy efficiency and quality in various computer subsystems. We classify approximate hardware techniques according to target subsystem and support for dynamic energy-quality scaling.