8 papers
Extracting and Verifying Illicit Bitcoin Addresses from Underground Forum Discussions
Abdoul Nasser Hassane Amadou, Arnaud Legout, Imane Fouad +2
Existing labeled Bitcoin datasets are largely derived from community-reported abuse, blockchain heuristics, incident-specific collections, or proprietary labeling processes. Their…
Can We Unmask the Underground? Detecting and Predicting Hidden Forum Interactions
Abdoul Nasser Hassane Amadou, Imane Fouad, Anas Motii
Cybercriminal underground forums enable anonymous collaboration, allowing users to trade illicit tools, discuss vulnerabilities, and distribute stolen data. Driven by shared intere…
Lightweight Intrusion Detection in IoT via SHAP-Guided Feature Pruning and Knowledge-Distilled Kronecker Networks
Hafsa Benaddi, Mohammed Jouhari, Nouha Laamech +2
The widespread deployment of Internet of Things (IoT) devices requires intrusion detection systems (IDS) with high accuracy while operating under strict resource constraints. Conve…
FakeZero: Real-Time, Privacy-Preserving Misinformation Detection for Facebook and X
Soufiane Essahli, Oussama Sarsar, Ahmed Bentajer +2
Social platforms distribute information at unprecedented speed, which in turn accelerates the spread of misinformation and threatens public discourse. We present FakeZero, a fully…
CyberNER: A Harmonized STIX Corpus for Cybersecurity Named Entity Recognition
Yasir Ech-Chammakhy, Anas Motii, Anass Rabii +2
Extracting structured intelligence via Named Entity Recognition (NER) is critical for cybersecurity, but the proliferation of datasets with incompatible annotation schemas hinders…
OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT
Saida Elouardi, Mohammed Jouhari, Anas Motii
In critical IoT environments, such as smart homes and industrial systems, effective Intrusion Detection Systems (IDS) are essential for ensuring security. However, developing robus…