Search Results for author: Satoru Momiyama

Found 4 papers, 0 papers with code

Latent SHAP: Toward Practical Human-Interpretable Explanations

no code implementations27 Nov 2022 Ron Bitton, Alon Malach, Amiel Meiseles, Satoru Momiyama, Toshinori Araki, Jun Furukawa, Yuval Elovici, Asaf Shabtai

Model agnostic feature attribution algorithms (such as SHAP and LIME) are ubiquitous techniques for explaining the decisions of complex classification models, such as deep neural networks.

Classification

On Brightness Agnostic Adversarial Examples Against Face Recognition Systems

no code implementations29 Sep 2021 Inderjeet Singh, Satoru Momiyama, Kazuya Kakizaki, Toshinori Araki

This paper introduces a novel adversarial example generation method against face recognition systems (FRSs).

Face Recognition

Dodging Attack Using Carefully Crafted Natural Makeup

no code implementations14 Sep 2021 Nitzan Guetta, Asaf Shabtai, Inderjeet Singh, Satoru Momiyama, Yuval Elovici

Deep learning face recognition models are used by state-of-the-art surveillance systems to identify individuals passing through public areas (e. g., airports).

Face Recognition

Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems

no code implementations5 Jul 2021 Ron Bitton, Nadav Maman, Inderjeet Singh, Satoru Momiyama, Yuval Elovici, Asaf Shabtai

Using the extension, security practitioners can apply attack graph analysis methods in environments that include ML components; thus, providing security practitioners with a methodological and practical tool for evaluating the impact and quantifying the risk of a cyberattack targeting an ML production system.

BIG-bench Machine Learning Graph Generation

Cannot find the paper you are looking for? You can Submit a new open access paper.