| Paper Abstract and Keywords |
| Presentation |
2025-03-05 13:15
[Poster Presentation]
An Investigation of Model Inversion Attacks on GAN-based Image Generator Yuka Ejiri, Kazuaki Nakamura (TUS) EMM2024-122 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Recently, the threat of cyber-attacks against machine learning models has increased. One example is the Model Inversion Attack (MIA). MIA is an attack that analyzes the outputs of a target model to estimate and reveal its training samples. So far, MIA methods have been actively studied on discriminative models. However, to the best of our knowledge, no existing MIA studies focus on generative models, which have been remarkably advancing in recent years. In this paper, as the first step in analyzing the risk of MIA on generative models, we propose an MIA method targeting a GAN-based image generator. The proposed method is based on the consideration that the density distribution of images generated by a target model has a local peak at the location of each training sample. Based on this consideration, the proposed method searches for the local peaks with the gradient descent algorithm to obtain MIA results similar to the training samples. The results show a certain level of attack capability of the proposed method. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
generative adversarial network / image generator / model inversion attack / density distribution / local maxima search / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 124, no. 414, EMM2024-122, pp. 28-33, March 2025. |
| Paper # |
EMM2024-122 |
| Date of Issue |
2025-02-26 (EMM) |
| ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| Download PDF |
EMM2024-122 |
| Conference Information |
| Committee |
EMM |
| Conference Date |
2025-03-05 - 2025-03-06 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Okinawaken Seinenkaikan |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
|
| Paper Information |
| Registration To |
EMM |
| Conference Code |
2025-03-EMM |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
An Investigation of Model Inversion Attacks on GAN-based Image Generator |
| Sub Title (in English) |
|
| Keyword(1) |
generative adversarial network |
| Keyword(2) |
image generator |
| Keyword(3) |
model inversion attack |
| Keyword(4) |
density distribution |
| Keyword(5) |
local maxima search |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Yuka Ejiri |
| 1st Author's Affiliation |
Tokyo University of Science (TUS) |
| 2nd Author's Name |
Kazuaki Nakamura |
| 2nd Author's Affiliation |
Tokyo University of Science (TUS) |
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| Speaker |
Author-1 |
| Date Time |
2025-03-05 13:15:00 |
| Presentation Time |
60 minutes |
| Registration for |
EMM |
| Paper # |
EMM2024-122 |
| Volume (vol) |
vol.124 |
| Number (no) |
no.414 |
| Page |
pp.28-33 |
| #Pages |
6 |
| Date of Issue |
2025-02-26 (EMM) |