Wenqing Yan

Research Activities

Ongoing Projects: 1. Ultra-low-power Receiver Design in Collaboration with Prof. Ambuj Varshney. 2. Harvesting the Unharvestable: Decoupling Transmitters Rethinks Wireless for Embedded Systems in Collaboration with Prof. Ambuj Varshney. 3. Fingerprint Devices in Backscatter Systems 4. On-board Fingerprinting System

Previous Projects:

JUDO: Addressing the Energy Asymmetry of Wireless Embedded Systems through Tunnel Diode based Wireless Transmitters
Teaser video Presentation video
ACM MobiSys2022, Portland, Oregon, USA.
Wenqing Yan
Prof. Ambuj Varshney*, National University of Singapore
Prof. Prabal Dutta, University of California, Berkeley
* Co-primary authors contributed equally to the work.
The radio transmitter is the most power-consuming component of a wireless embedded system. We present JUDO, a radio transmitter that enables power balance between the wireless transmission, sensing, and processing tasks of a wireless embedded system. In this work, we revisit the radio transmitter architecture by dramatically reducing the radiated power and hence the overall power draws. Specifically, JUDO transmitters use a tunnel diode oscillator to integrate the stages of a radio transmitter into a single energy-efficient step. In this step, baseband signals are generated and mixed with peak power draws below 100 mW. However, tunnel diode oscillators sacrifice stability for low-power, which we sidestep by using injection-locking to stabilize the tunnel diode oscillator with an external carrier signal. Based on this novel architecture, we implement a transmitter that supports frequency-shift keying as a modulation scheme. JUDO transmits to a receiver over distances exceeding 100 m at a bit rate of 100 kbps. Crucially, it does so with an emitter device providing the carrier signal, also located more than 100 m from the JUDO transmitter. In terms of critical link metrics, JUDO outperforms the radio transmitters commonly used in wireless embedded systems.

RRF: A Robust Radiometric Fingerprint System that Embrace Wireless Channel Diversity
Teaser video Presentation video
ACM WiSec2022, San Antonio, Texas, USA.
Wenqing Yan,
Prof. Christian Rohner, Uppsala University
Prof. Thiemo Voigt, Uppsala University, RISE Research Institutes of Sweden
Radiometric fingerprint schemes have been shown effective in identifying wireless devices based on imperfections in their hardware electronics. The robustness of fingerprint systems under complex channel conditions, however, is a critical challenge that makes their application in real-world scenarios difficult. We systematically evaluate the wireless channel impact on radiometric fingerprints and find that the channel impacts fingerprint features in a very particular way that depends on the channel properties. Based on these insights, we present RRF, a system that provides a robust identification/authentication service even under complex channel fading disturbance. Our design deploys a hybrid architecture that combines wireless channel simulation, signal processing and machine learning.

Decomposing Radiometric Fingerprints in Backscatter Systems
Wenqing Yan,
Prof. Christian Rohner, Uppsala University
Prof. Thiemo Voigt, Uppsala University, RISE Research Institutes of Sweden
Radiometric fingerprinting is an effective technique for identifying and authenticating wireless devices by leveraging unique imperfections in transmitter electronics. This approach fits well with the low-power and low-complexity philosophy of backscatter systems because their purely passive nature requires no extra resources. Backscatter systems delegate the power-intensive generation of the carrier to an external emitter device and modulate the data by reflecting carrier signals at a low-power tag. In this paper, we systematically analyze the backscatter architecture and decompose the fingerprint, allowing us to accurately distinguish and classify both tags and carrier emitters with a true accept ratio of over 98.4\% and below 1.6\% false accept ratio.

PHY-IDS: A Physical-layer Spoofing Attack Detection System for Wearable Devices
Presentation video
ACM WearSys Workshop in conjuction with MobiSys2020, Toronto, Canada.
Wenqing Yan
Prof. Christian Rohner, Uppsala University
Prof. Thiemo Voigt, Uppsala University, RISE Research Institutes of Sweden
In modern connected healthcare applications, wearable devices supporting real-time monitoring and diagnosis have become mainstream. However, wearable systems are exposed to massive cyber-attacks that threaten not only data security but also human safety and life. One of the fundamental security threats is device imper- sonation. We therefore propose PHY-IDS; a lightweight real-time detection system that captures spoofing attacks leveraging on body motions. Our system utilizes time series of physical layer features and builds on the fact that it is non-trivial to inject malicious frames that are indistinguishable with legitimate ones. With the help of statistical learning, our system characterizes the signal behavior and flags deviations as anomalies. We experimentally evaluate PHY-IDS’s performance using bodyworn devices in real attack scenarios. For four types of attackers with increasing knowledge of the deployed detection system, the results show that PHY-IDS detects naive attackers with high accuracy above 99.8% and maintains good accuracy for stronger attackers at a range from 81.0% to 98.9%.