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20172026
most citedMEGEX: Data-Free Model Extraction Attack against Gradient-Based Explainable AI

11 citations · 12 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CR2023

On Rényi Differential Privacy in Statistics-Based Synthetic Data Generation

Takayuki Miura, Toshiki Shibahara, Masanobu Kii +3

Privacy protection with synthetic data generation often uses differentially private statistics and model parameters to quantitatively express theoretical security. However, these m…

cs.CR2023

Do Backdoors Assist Membership Inference Attacks?

Yumeki Goto, Nami Ashizawa, Toshiki Shibahara +1

When an adversary provides poison samples to a machine learning model, privacy leakage, such as membership inference attacks that infer whether a sample was included in the trainin…

cs.CR2022

Interpreting Graph-based Sybil Detection Methods as Low-Pass Filtering

Satoshi Furutani, Toshiki Shibahara, Mitsuaki Akiyama +1

Online social networks (OSNs) are threatened by Sybil attacks, which create fake accounts (also called Sybils) on OSNs and use them for various malicious activities. Therefore, Syb…

cs.CR2021★ 11 cited

MEGEX: Data-Free Model Extraction Attack against Gradient-Based Explainable AI

Takayuki Miura, Satoshi Hasegawa, Toshiki Shibahara

The advance of explainable artificial intelligence, which provides reasons for its predictions, is expected to accelerate the use of deep neural networks in the real world like Mac…

cs.CR2017★ 1 cited

A Study on the Vulnerabilities of Mobile Apps associated with Software Modules

Takuya Watanabe, Mitsuaki Akiyama, Fumihiro Kanei +7

This paper reports a large-scale study that aims to understand how mobile application (app) vulnerabilities are associated with software libraries. We analyze both free and paid ap…