Honorable Mention
We engineered a wearable microphone jammer that is capable of disabling microphones in its user's surroundings, including hidden microphones. Our device is based on a recent exploit that leverages the fact that when exposed to ultrasonic noise, commodity microphones will leak the noise into the audible range.<br>Unfortunately, ultrasonic jammers are built from multiple transducers and therefore exhibit blind spots, i.e., locations in which transducers destructively interfere and where a microphone cannot be jammed. To solve this, our device exploits a synergy between ultrasonic jamming and the naturally occur- ring movements that users induce on their wearable devices (e.g., bracelets) as they gesture or walk. We demonstrate that these movements can blur jamming blind spots and increase jamming coverage. Moreover, current jammers are also directional, requiring users to point the jammer to a microphone; instead, our wearable bracelet is built in a ring-layout that al- lows it to jam in multiple directions. This is beneficial in that it allows our jammer to protect against microphones hidden out of sight.<br>We evaluated our jammer in a series of experiments and found that: (1) it jams in all directions, e.g., our device jams over 87% of the words uttered around it in any direction, while existing devices jam only 30% when not pointed directly at the microphone; (2) it exhibits significantly less blind spots; and, (3) our device induced a feeling of privacy to participants of our user study. We believe our wearable provides stronger privacy in a world in which most devices are constantly eavesdropping on our conversations.
https://doi.org/10.1145/3313831.3376304
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)