@inproceedings{94ffc2ca403d4c31a99301727f93575f,
title = "A New D-MAGIC: Dynamic Model for Cybersecurity Attack Detection Using GNNs into Clustering",
abstract = "The increasing sophistication and frequency of cyberattacks have made Network Intrusion Detection Systems (NIDS) a critical component of modern cybersecurity. This work presents D-MAGIC, a novel real-time NIDS that leverages zero-shot learning and graph-based dynamic clustering to detect known and unknown threats. Unlike traditional systems that rely on labeled datasets and predefined attack signatures, D-MAGIC operates unsupervised, identifying anomalies by detecting deviations from normal network behavior. By embedding the relationships between network flows into a graph structure and dynamically clustering similar patterns, D-MAGIC can detect coordinated attacks and emerging threats with minimal delay. Experimental results on the CIC-IDS-2017 and CSE-CIC-IDS-2018 datasets demonstrate that D-MAGIC achieves an improvement of up to 12\% based on the standard F1 score compared to state-of-the-art methods, while significantly reducing false positives and ensuring rapid, real-time detection with minimal detection latency.",
keywords = "Anomaly detection, Clustering, Deep learning, GNNs, Real-time Network Intrusion Detection Systems, Unsupervised-learning",
author = "Zohar Simhon and Matan Weiss and Chen Hajaj and Revital Marbel and Ran Dubin and Amit Dvir",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE International Conference on Communications, ICC 2025 ; Conference date: 08-06-2025 Through 12-06-2025",
year = "2025",
doi = "10.1109/ICC52391.2025.11160734",
language = "אנגלית",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6771--6776",
editor = "Matthew Valenti and David Reed and Melissa Torres",
booktitle = "ICC 2025 - IEEE International Conference on Communications",
address = "ארצות הברית",
}