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Adversarial Machine Learning Against Voice Assistant Systems
Adversarial Machine Learning Against Voice Assistant Systems
WINLAB Summer Internship 2022
Group Members: Matt Kokolus
Project Objective
This project aims to study the security of voice assistant systems under adversarial machine learning. Adversarial learning algorithms can generate adversarial audio samples to serve as the input of voice assistant systems, so as to fool the machine learning models in the system. In this project, students will focus on the white-box attack in the digital domain by generating adversarial samples using adversarial machine learning algorithms to attack a speaker recognition system based on X-Vector. The students will learn Python with Tensorflow Library.
Attachments (3)
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Practical Adversarial Attacks.pdf
(2.4 MB
) - added by 2 years ago.
Practical Adversarial Attacks Against Speaker Recognition Systems
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Hidden Voice Commands.pdf
(743.3 KB
) - added by 2 years ago.
Hidden Voice Commands
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Final Poster - Voice Assistant.pptx.pdf
(1.1 MB
) - added by 2 years ago.
Final Research Poster