11 citations · 12 across the 7 of their papers we have counts for
7 papers
The Impact of Micro-level User Interventions on Macro-level Misinformation Spread
Satoshi Furutani, Toshiki Shibahara, Mitsuaki Akiyama
User interventions such as nudges, prebunking, and contextualization have been widely studied as countermeasures against misinformation, and shown to suppress individual users' sha…
Network Prebunking Problem: Optimizing Prebunking Targets to Suppress the Spread of Misinformation in Social Networks
Satoshi Furutani, Toshiki Shibahara, Mitsuaki Akiyama +1
As a countermeasure against misinformation that undermines the healthy use of social media, a preventive intervention known as \textit{prebunking} has recently attracted attention…
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…
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…
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…
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…
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…