8 citations · 13 across the 7 of their papers we have counts for
7 papers
IC-SECURE: Intelligent System for Assisting Security Experts in Generating Playbooks for Automated Incident Response
Ryuta Kremer, Prasanna N. Wudali, Satoru Momiyama +4
Security orchestration, automation, and response (SOAR) systems ingest alerts from security information and event management (SIEM) system, and then trigger relevant playbooks that…
Simultaneous Adversarial Attacks On Multiple Face Recognition System Components
Inderjeet Singh, Kazuya Kakizaki, Toshinori Araki
In this work, we investigate the potential threat of adversarial examples to the security of face recognition systems. Although previous research has explored the adversarial risk…
Advancing Deep Metric Learning Through Multiple Batch Norms And Multi-Targeted Adversarial Examples
Inderjeet Singh, Kazuya Kakizaki, Toshinori Araki
Deep Metric Learning (DML) is a prominent field in machine learning with extensive practical applications that concentrate on learning visual similarities. It is known that inputs…
Latent SHAP: Toward Practical Human-Interpretable Explanations
Ron Bitton, Alon Malach, Amiel Meiseles +5
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 n…
Powerful Physical Adversarial Examples Against Practical Face Recognition Systems
Inderjeet Singh, Toshinori Araki, Kazuya Kakizaki
It is well-known that the most existing machine learning (ML)-based safety-critical applications are vulnerable to carefully crafted input instances called adversarial examples (AX…
Universal Adversarial Spoofing Attacks against Face Recognition
Takuma Amada, Seng Pei Liew, Kazuya Kakizaki +1
We assess the vulnerabilities of deep face recognition systems for images that falsify/spoof multiple identities simultaneously. We demonstrate that, by manipulating the deep featu…