Hello, everyone.
Welcome to my presentation.
Today, I’m gonna present our paper,
“Anti-Spoofing Voice Commands: A Generic Wireless Assisted Design”.
This is the content for the presentation, so first I will talk about the motivation
and then elaborate the system design and evaluation.
Voice to user interfaces, like Apple Siri, Google Assistant, Amazon Alexa, are becoming
popular in recent years.
More and more devices could be controlled through these VUIs,
such as the access control of devices at smart home, entrance guard system and automobiles.
However, sound travels through an open channel, which is vulnerable to eavesdropping and replay attack.
So there is an urgent need of the ability to accept voice commands from live legal users.
In the literature, verifying live and legal users these two aspects has been studied separately.
The user’s identity can be verified by extracting user-specific features from voice commands
like the MFCC.
To verify a live user, we can ask the VUI device to transmit certain signals to capture
the user’s body movement, to defend the attack of replaying the legal user’s voice.
However, a direct combination of liveness detection and identification, for example,
a dual-channel countermeasure, is still inadequate.
The attacker can replay both the voice command and sensing signal simultaneously to compromise the system,
Because the safety of the sensing channel itself is ignored in previous designs.
Moreover, the attacker also can replay a recorded voice command and mimic the user’s body
movements to fool the system, because most of the liveness detection only
ensure that a person is indeed speaking, but they do not consider the identity of the current speaker.
As a result, we introduce WISE to address these challenges.
WISE is an enhanced dual-channel method, which can support different types of sensing signals,
and defend against many crucial attacks.
WISE contains three main modules: Sensing interface captures the user’s mouth
movements during speaking to defend the replay attack on the voice command.
It is a generic interface to cooperate with different wireless signals, such as RFID,
Wi-Fi and acoustic signals.
Transceiver sheltering uses the one-time random noise to “pollute” the sensing signal,
and only the VUI device itself knows how to recover the signal each time.
Such a mechanism makes WISE further resilient to the dual-channel replay attack.
In particular, For RFID, we modify the traditional constant continuous wave to a noise-like sequence
to hide the tag’s EPC reply, which is known to the reader only.
Such a modification is able to activate the tag but undermines the EPC decoding,
unless this noise can be canceled precisely.
For a clear illustration, we only modify the first half of the continuous wave in figure A.
be eliminated, the recovered signal can still be decoded correctly.
In the frequency domain, the EPC is also hidden well, as shown in figure C and D.
For Wi-Fi, we propose to rotate a random degree on the constellation diagram for each transmission packet,
and only a legal receiver knows how to rotate them back.
To ensure the detection of the incoming packet at the receiver, we skip the preamble field.
In general, the probability to crack the rotation for one packet is not very small, about 4 percent.
However, when a user speaks one voice command, there will be 1000 packets received per second
and the cracking probability becomes very small.
To enable above noise addition for acoustic signals, we make an acoustic-based transmission
by employing the OFDM technique and the key parameters are listed in the Table.
As a result, our transceiver sheltering module of Wi-Fi can be transplanted to the acoustic
based WISE directly.
Finally, we adopt a neural network to verify whether the received voice command is spoken
by a person and whether this live user is a legal user.
Since the voice command and sensing signal all contribute to identify a user, WISE can
defend against replaying voice command and mimicking the user’s mouth movements simultaneously.
We implement WISE by using RFID, Wi-Fi and inaudible sound three types of sensing signals.
And we evaluate the system performance in six environments.
In the evaluation,
Figure A reports the accuracy of verifying 12 live legal users, which is above 90% in
all the six environments.
While figure B and C suggest that WISE can effectively reject an attacker who mimics
or replays the voice of a legal user to compromise the system.
Figure D shows that replaying both user’s voice recording and sensing signal is still
invalid for WISE and over 99% of the dual-channel replay attacks are early rejected by our transceiver sheltering module.
This is the conclusion.
Thanks for listening.