Literature Database

文献データベースでは、AIセキュリティに関する文献情報を分類・集約しています。詳しくは文献データベースについてをご覧ください。統計情報のページでは、収集された文献に関する統計情報を公開しています。

The Literature Database categorizes and aggregates literature related to AI security. For more details, please see About Literature Database. We provide statistical information regarding the Literature Database on the Statistics page.

Literature Database

Forensic-Oriented Intrusion Detection Using Synthetic Network Traffic Data and Explainable Artificial Intelligence

HARC: Coupling Harmfulness and Refusal Directions for Robust Safety Alignment

Cross-Domain Generalization Failure in Lightweight Intrusion Detection Models for IIoT Networks

Beyond the Prompt: Jailbreaking Function-Calling LLMs via Simulated Moderation Traces

Predicting Lethal Outcome (Cause) And Understanding Key Biomarkers Linked With Acute Myocardial Infarction Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

A Penny for Your Prompts: Experiments Detecting and Mitigating LLM Usage by Survey Respondents

SoK: Attack and Defense Landscape of Mobile On-device AI Systems

What’s Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models

FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning

A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems