Hi everyone, my name is Yuxin. Today, Shan-Yuan and I are going to talk about
the idea of wearable microphone jamming
This is on behalf of our colleagues, Huiying, Steven, Zhijing
and our advisors, Pedro, Ben, and Heather, at the University of Chicago
This idea is about using a wearable to disable microphones in its user's surroundings
And I want to show you directly what I am talking about
"so, how does it work?"
"I can tell you how it works,"
"but it's confidential."
As you can see here
these two people are having some private conversation and to protect their privacy
she is going to turn on the privacy bracelet
As s result, the camera only recorded this junk white noise. And this noise is so loud that
it disables the microphone’s ability to do any useful recordings.
Besides the camera, other microphones in the scene are also disabled.
like his smartphone his smartwatch
and this voice assistant And I want to play the rest of the video
as you will see, they are still having normal conversation.
this is because this noise, is something that somehow only the microphones
can hear, but not humans
so why we do need a microphone jammer
today, microphones are everywhere like the voice assistant right here
they are also in your kitchen, they are even in your car,
but, unfortunately, these microphone-based devices are not secure
they can be easily attacked here is an example discovered by a previous
study this user is talking to the voice assistant
and the top left corner shows the attacker’s screen
"Alexa, stop."
"Goodbye."
"I will vote democrats."
this is just one basic attack
there are several more advanced attacks out there
So how can we protect ourselves against these privacy threats?
one promising way that researchers have been looking at is to
disable, to jam microphones A simple idea is to blast super loud noise
into the room to cover human voice
like the white noise generator here but this is not effective because it also
disrupts human conversation Recently, Roy and his colleagues found a new
way to jam microphones. they use inaudible ultrasound, instead of
using audible noise and let me tell you how it works
So microphones are designed to only record sounds that human can hear
Ideally ultrasound should not be captured But, in fact, when ultrasound passes through
the microphone it automatically gets shifted to
the low frequency band And this is because of hardware defect
which is the non linearity of microphone’s amplifier
with this property, we can send ultrasound to cover human voice
without interrupting normal conversation and you can even buy these devices on the
market They work well
microphones close to these devices can be jammed
but they share three limitations the first one is that they are all stationary
device So they do not go with user
and the second one is that they have limited angular coverage
you need to point them to the target microphone to jam
if you don’t know where the microphone is then the jammer will not work
even you know where the microphone is, your primary task as an user,
is not doing whatever you are doing, like having a conversation
but instead, your primary task is to looking at things and then point the jammer
to the target microphone another thing makes this even harder
is that the jamming coverage is not evenly distributed
there are some blind spots where the jamming signal is so weak
like the white spots right here this is because these ultrasonic jammers are
relying on multiple transducers to increase their power and coverage
So signal from different transducers are destructively interfered with each other
at some points some locations
and create blind spots this means you need to point it fairly precisely
otherwise, you are going to point it in the blind spots
and the jammer will not work so to tackle these three problems
we turn ultrasonic jammer into a wearable jammer
let me show you how this solves all the problems I just mentioned
first of all it’s a wearable,
so it moves with the user, and it protects the user’s surroundings
we use a ring layout instread of a planar layout
and place ultrasonic speaker all around this design effectively enables multi directional
jamming. we ran a simulation, to see how these things
work this figure shows the jamming power of a
90 degree area the jammer is placed in the bottom left corner,
and point to the top blue means weak jamming, and yellow means
strong jamming as you can see here,
the planar layout has limited coverage it mostly jam in the front
and also has blind spots for our ring layout,
it covers all the directions but there still have several blind spots
so we found that adding small motion to the jammer
can blur out these blind spots by building a wearable jammer,
we can leverage natural hand gestures, to reduce blind spots
we also ran a simulation, to confirm our findings
I will let Shan-Yuan to take over and tell you how we implement this wearable jammer
Hi, I'm Shan-Yuan Teng Let me walk you through the implementation
of our wearable jammer. We designed our wearable jammer in a bracelet
form where we placed all the ultrasonic transducers
in a ring layout. Inside the casing
you see our custom circuit We used a programmable microcontroller,
connect it to a signal generator where we programmed to generate random sine
wave that centered around the resonance frequency of the transducers.
That is, we sweep between 24khz to 26khz. They are all in human inaudible range.
And then, we amplify th signal through an amplifier.
Finally, our circuit and transducers are powered using a lithium battery, that supports 4 hour
of continuous jamming So if I turn this on, this will generate ultrasound
that produce an audible noise for the microphone of this camera that is recording me
But I will not hear it. So let me turn this on
...off, now you can hear me again Let me show you how we evaluate our prototype
through three technical evaluations and a user study
I'll just focus on highlight today this experiment is to understand how well
our prototype jams state-of-the-art speech recognizer.
we place an audio speaker near our prototype and playback human speech from a large corpus
To approximate hand movement, we put our prototype on a motion platform that slightly rotates,
and let it jammed continuously. Then we recorded the audio using the smartphone
that was put 1 meter away we piped the audio to a state-of-the-art machine
learning speech recognizer, which is IBM cloud that we used, and see how much text is able
to be identified we moved our smartphone around the jammer
to measure the jamming coverage every 5 degrees from the front to the rear
Then we ran the same experiment with i4, the existing commercial product.
And a planar layout, which we find in the literature
Here’s the result of our wearable jammer. The x axis is the the different angles we
measured. The y-axis is the word error rate that we found by comparing the speech recognition
result and the corpus scripts. This shows how many words are recognized incorrectly.
the higher the better jamming performance. We see our wearable jammer jammed pretty well
in all the angles Here is an example of the data. This is the
original speech we played And this is the recorded audio with our jamming
We see only the two first words can be recognized. Other words are either being recognized as
wrong words or the recognizer just completely missed it.
Resulting in a high word error rate The grey line is the jamming result of i4,
the commercial product, It not only shows that the jamming coverage
is very limited But also there’s a clear blind spot in its
coverage, where much less words are jammed. The planar layout, shown in this black line,
also has similar trends With limited coverage
And a blind spot Compared to the other two jammers, our wearable
prototype has wide coverage and similarly well jamming performance
However, in this experiment, we were controlling all the environment variables, and the corpus
is scripted, and there are no real users. We decided to invite users to use our prototype
We wanted to understand whether wearing our jamming bracelet impacts one’s feeling of
privacy in a natural setting. The participants we recruited were asked to
have free-form conversations, which were not scripts. They exchanged the bracelet in the
conversation, while the phones on the table were recording.
After the conversation, participants were given transcripts, which were generated using
speech recognition, from the phone’s recording We find that participants felt that our bracelet
protected their privacy, rating an average of 5.4 out of 7. We interviewed the participants,
Some said the bracelet was noticeable but they forgot about it or stopped feeling
odd about wearing it once they focused on the conversation
Some felt more protected either when wearing the bracelet or by simply seeing others wearing it
I’ll let Yuxin to wrap up our talk.
To conclude, we design, implement a wearable ultrasonic
jammer to protect you all around against eavesdropping
microphones And the jammer has full angular coverage
And minimizes blind spots As we are all surrounded by microphones all
the time Our wearable jammer provides users a practical
and effective tool to protect their privacy We believe this is a great start point
And it also opens new directions for new researches, including understanding its influence to animals,
testing on more microphones, increasing its vertical coverage
and building in other form factors. Now I want to thank our colleagues and our
advisors. Thank you