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An Empirical Study on the Transferability of Transformer-Based Models for Software Vulnerability Detection
Despite the dominance of Transformer-based models in software vulnerability detection, the extent to which their learned security logic generalizes across different programming languages remains…
Xem chi tiếtGraph-Driven LLM-Augmented Stateful API Fuzzing for OWASP API Top 10
Security testing of REST APIs remains difficult because real-world OpenAPI specifications are often incomplete, many security flaws are inherently stateful, and prevailing stateful fuzzers…
Xem chi tiếtA Class-incremental and Few-shot learning model for Intrusion detection under Concept drift
Network Intrusion Detection Systems (NIDS) based on machine learning must evolve after deployment to detect emerging threats very soon with a few labeled samples,…
Xem chi tiếtMORPH-IDS: A Context-Driven Multi-Agent Reinforcement Learning Framework for Drift-Aware Moving Target Defense in Adversarial-Robust Intrusion Detection
In the rapidly evolving cybersecurity landscape, Machine Learning (ML)-based Network Intrusion Detection Systems (NIDS) have become essential for detecting sophisticated threats, yet they are…
Xem chi tiếtXDFC-IDS: An Explainable Decentralized Federated Class-Incremental Fusion Framework for Intrusion Detection
With the widespread adoption of IoT and edge computing, federated learning (FL)-based intrusion detection systems (IDSs), which enable privacy-preserving, cost-effective training by fusing knowledge…
Xem chi tiếtPoisoning the Swarm: Evaluating Data-Level Vulnerabilities in Decentralized Internet of Medical Things-enabled Healthcare Networks
Swarm Learning (SL) integrates federated learning and blockchain to support decentralized privacy-preserving learning for smart healthcare. However, the resilience of its learning and aggregation…
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