ANALYSIS OF MULTIPLE ADVERSARIAL ATTACKS ON CONVOLUTIONAL NEURAL NETWORKS

Author

Burcum EkenFollow

Date of Award

8-2022

Degree Type

Thesis

Degree Name

Master of Science

Major

Computer Engineering

Major Professor

Seddik M. Djouadi

Committee Members

Kevin Tomsovic, Jinyuan “Stella” Sun

Abstract

The thesis studies different kind of adversarial attacks on Convolutional Neural Network by using electric load data set in order to fool deep neural network. With the improvement of Deep Learning methods, their securities and vulnerabilities have become an important research subject. An adversary who gains access to the model and data sets may add some perturbations to the datasets, which may cause significant damage to the system. By using adversarial attacks, it shows how much these attacks affect the system and shows the attacks' success in this research.

Recommended Citation

Eken, Burcum, "ANALYSIS OF MULTIPLE ADVERSARIAL ATTACKS ON CONVOLUTIONAL NEURAL NETWORKS. " Master's Thesis, University of Tennessee, 2022.
https://trace.tennessee.edu/utk_gradthes/6460