Title

Adversarial Perturbation Suppression Using Adaptive Gaussian Smoothing and Color Reduction

Published In

2021 IEEE International Symposium on Multimedia (ISM)

Document Type

Citation

Publication Date

12-2021

Abstract

This paper presents a novel context-aware image denoising algorithm that combines an adaptive image smoothing technique and color reduction techniques to remove perturbation from adversarial images. Adaptive image smoothing is achieved using auto-threshold canny edge detection to produce an accurate edge map used to produce a blurred image that preserves more edge features. The proposed algorithm then uses color reduction techniques to reconstruct the image using only a few representative colors. Through this technique, the algorithm can reduce the effects of adversarial perturbations on images. We also discuss experimental data on classification accuracy. Our results showed that the proposed approach reduces adversarial perturbation in adversarial attacks and increases the robustness of the deep convolutional neural network models.

Rights

Copyright 2021 IEEE

DOI

10.1109/ISM52913.2021.00033

Persistent Identifier

https://archives.pdx.edu/ds/psu/37012

Publisher

IEEE

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