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ADCC-Bench: A Benchmark Framework for Anomaly Detection in Cryptocurrency Transactions

A Method for Secure Verification and Classification of Educational Credentials based on Zero-Knowledge Range Proof

A Multimodal Approach for Windows Malware Detection using Comprehensive Analysis on Called APIs

With the continuous evolution of the Windows operating system, malware-especially those based on Portable Executable (PE) files-has become increasingly sophisticated. Recent studies have widely…

PhishFusion: A Multimodal Phishing Website Detection Framework using Joint URL and JavaScript Features

Leveraging LLMs to Support Malware Analysis from Structured and Semantic Binary Data

A study on functionality validation for windows malware mutating using reinforcement learning

To keep pace with the rapid advancements in both the quality and complexity of malware, recent research has extensively employed machine learning (ML) and…

xPriMES: Explainable Reinforcement Learning-guided Mutation Strategy with Dual-Environment Interaction for Evading Black-box Malware Detectors

Malware continues to evolve, exposing weaknesses in conventional detectors and motivating realistic adversarial evaluations. Prior RL-based evasion methods often rely on partial model access…

Android malware detection by using graph optimization of static features based on pre-trained language models

The Android platform is the dominant mobile operating system, making it a prime target for malware attacks. The increasing complexity of Android malware necessitates…

Hawkeyes: An Intelligent Honeypot Allocation Strategy for Cyber Deception using Reinforcement Learning

Honeypot allocation has emerged as a pivotal strategy in cyber deception. However, existing approaches often face scalability issues, limited coordination, and inadequate consideration of…