Quantum machine learning (QML) has emerged as a promising paradigm for intrusion detection systems (IDS) in resource-constrained and highly dynamic IoT networks due to…
Xem chi tiếtLarge Language Models (LLMs) have emerged as powerful tools for software vulnerability detection, yet their decision-making processes remain opaque and highly sensitive to prompt…
Xem chi tiếtDigital forensic investigation requires the correlation of large volumes of heterogeneous host and network telemetry while preserving evidentiary consistency. Large Language Model (LLM) agents…
Xem chi tiếtSmart contracts secure high-value blockchain applications, yet vulnerabilities continue to cause severe financial losses, making automated detection critical. While large language models (LLMs) show…
Xem chi tiếtLarge Language Models (LLMs) for code are increasingly used for software vulnerability detection, yet security review requires more than a correct Vulnerable or Safe…
Xem chi tiếtAlthough Domain Generation Algorithm (DGA) detectors often achieve strong performance under closed-set evaluation, deployed systems must also handle previously unseen DGA families and heterogeneous…
Xem chi tiếtWith the rise of complex attacks, traditional web honeypots struggle to maintain authenticity due to static and easily fingerprinted responses. This paper presents a…
Xem chi tiếtIn recent years, Android malware detection has advanced rapidly with the adoption of learning-based techniques, which typically analyze app code as text, images, or…
Xem chi tiếtIntrusion Detection Systems (IDS) play a crucial role in safeguarding computer networks against malicious activities. However, current IDS models based on machine learning (ML)…
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