| Paper Abstract and Keywords |
| Presentation |
2025-06-05 15:50
Comparative Analysis of Attack and Defense Methods Against Learned Image Compression Models
Jun Kurihara, Heming Sun (YNU) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In recent years, learned image compression (LIC) models have attracted attention as a promising approach for achieving high-efficiency image compression. However, a key challenge of such machine learning-based models is their vulnerability to adversarial perturbations, which can significantly degrade the quality of the reconstructed images. In this study, we evaluate the performance of an adversarial attack using the Fast Gradient Sign Method (FGSM) as well as a defense method based on adversarial training. For the attack, we define three different loss functions based on the combinations of the original, perturbed, and reconstructed images, and compare the attack performance of FGSM under each loss. The results show that using the loss between the original and reconstructed images for gradient computation yields the most effective attack. For the defense, adversarial training is applied to the LIC model using adversarial examples. This approach successfully mitigates the degradation of the reconstructed images and improves the rate-distortion performance by 11.4% compared to the model before training. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
LIC model / Adversarial Attack / Adversarial Training / FGSM / / / / |
| Reference Info. |
ITE Tech. Rep. |
| Paper # |
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| Date of Issue |
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| ISSN |
Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
IST ME IEICE-IE IEICE-BioX IEICE-SIP IEICE-MI |
| Conference Date |
2025-06-05 - 2025-06-06 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
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| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
IEICE-IE |
| Conference Code |
2025-06-IST-ME-IE-BioX-SIP-MI |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Comparative Analysis of Attack and Defense Methods Against Learned Image Compression Models |
| Sub Title (in English) |
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| Keyword(1) |
LIC model |
| Keyword(2) |
Adversarial Attack |
| Keyword(3) |
Adversarial Training |
| Keyword(4) |
FGSM |
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| 1st Author's Name |
Jun Kurihara |
| 1st Author's Affiliation |
Yokohama National University (YNU) |
| 2nd Author's Name |
Heming Sun |
| 2nd Author's Affiliation |
Yokohama National University (YNU) |
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| Speaker |
Author-1 |
| Date Time |
2025-06-05 15:50:00 |
| Presentation Time |
25 minutes |
| Registration for |
IEICE-IE |
| Paper # |
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| Volume (vol) |
vol.49 |
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