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Results for "attack detection"

LLM-based Multi-class Attack Analysis and Mitigation Framework in IoT/IIoT Networks

arXiv · Oct 30

This paper introduces a framework that combines machine learning for multi-class attack detection in IoT/IIoT networks with large language models (LLMs) for attack behavior analysis and mitigation suggestion. The framework uses role-play prompt engineering with RAG to guide LLMs like ChatGPT-o3 and DeepSeek-R1, and introduces new evaluation metrics for quantitative assessment. Experiments using Edge-IIoTset and CICIoT2023 datasets showed Random Forest as the best detection model and ChatGPT-o3 outperforming DeepSeek-R1 in attack analysis and mitigation.

Scientists Develop Ground-breaking Deep Learning Model for Real-time Security Environments

TII · Mar 17

Researchers including Dr. Najwa Aaraj developed ML-FEED, a new exploit detection framework using pattern-based techniques. The model is 70x faster than LSTMs and 75,000x faster than Transformers in exploit detection tasks, while also being slightly more accurate. The "ML-FEED" paper won best paper at the 2022 IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications. Why it matters: This research enables more efficient real-time security applications and highlights growing AI expertise in the Arab world.

UAE faces up to 700,000 cyberattacks a day amid regional tensions - Gulf News

The National · Mar 30

The United Arab Emirates is reportedly experiencing a high volume of cyberattacks, reaching up to 700,000 incidents daily, as reported by Gulf News. These attacks are occurring amid heightened regional tensions, indicating a sophisticated and persistent threat landscape. This ongoing situation poses significant challenges to the UAE's digital infrastructure and national security. Why it matters: This high frequency of cyberattacks underscores the critical need for advanced cybersecurity measures and the potential for AI-driven defense solutions in the region to protect vital infrastructure and data amidst geopolitical instability.