Changes between Version 9 and Version 10 of Other/Summer/2020/AdvML


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Timestamp:
Jun 8, 2020, 2:50:15 PM (4 years ago)
Author:
yb220
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  • Other/Summer/2020/AdvML

    v9 v10  
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    33== Project Objective ==
    4 This project aims to study the security of voice assistance systems under adversarial machine learning. The audio adversarial samples generated by adversarial learning algorithms can be played via a loudspeaker and recorded with the microphone of voice assistance systems so as to fool the machine learning models in the system. To make the adversarial samples robust under audio propagation, the room impulse response needs to be estimated and used in the adversarial sample generation process. Specifically, the room impulse response and adversarial attack scenarios can be conducted in digital domain or simulated for the over-the-air scenarios using Python or Matlab.
     4This 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, we 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. If time allows, we will further enhance the robustness of the attack by simulating room impulse response and conduct over-the-air attack.
    55
    66== Tutorials ==
     7*Week 1
    78- Generating Adversarial Samples in Keras: https://medium.com/mindboard/generating-adversarial-samples-in-keras-tutorial-f881ac836246
    89- Tensorflow - Adversarial Example using FGSM: https://www.tensorflow.org/tutorials/generative/adversarial_fgsm 
    910- Generating Adversarial Samples in Keras: https://medium.com/analytics-vidhya/implementing-adversarial-attacks-and-defenses-in-keras-tensorflow-2-0-cab6120c5715
     11*Week 2
     12- Python tutorial: https://www.w3schools.com/python/
     13- How to run Python code: https://www.knowledgehut.com/blog/programming/run-python-scripts
     14- Jupyter notebook tutorial: https://www.dataquest.io/blog/jupyter-notebook-tutorial/
     15- Video tutorial (Optional): Neural Networks and Deep Learning: https://www.coursera.org/learn/neural-networks-deep-learning
    1016
    1117== Reading Material ==
    … …  
    2935
    3036== Week2 Tutorials ==
    31 - Python tutorial: https://www.w3schools.com/python/
    32 - How to run Python code: https://www.knowledgehut.com/blog/programming/run-python-scripts
    33 - Jupyter notebook tutorial: https://www.dataquest.io/blog/jupyter-notebook-tutorial/
    34 - Video tutorial (Optional): Neural Networks and Deep Learning: https://www.coursera.org/learn/neural-networks-deep-learning