@inproceedings{13ffb2fdaa5f40949968617c8a1ca3d0,
title = "AI-Driven Intrusion Detection for Secure IoT Communication",
abstract = "The rapid adoption of IoT device, has introduced unprecedented security challenges, necessitating robust intrusion detection systems. This work presents an artificial intelligence-driven architecture for intrusion detection in IoT network. The model uses a CNN-based architecture for intrusion detection. The experiment analysis shows the accuracy of 90.6\%, which is more than the baseline model.",
keywords = "CNN Model, Intrusion Detection, IoT Attack Detection",
author = "Akshat Gaurav and Hsu, \{Ching Hsien\} and Chui, \{Kwok Tai\} and Gupta, \{Brij B.\}",
note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 13thIEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2026 ; Conference date: 01-07-2026 Through 03-07-2026",
year = "2026",
doi = "10.1109/ICCE-TAIWAN71481.2026.11652381",
language = "English",
series = "ICCE-TW 2026 - The 13th IEEE International Conference on Consumer Electronics - Taiwan: Sustainable and Human-centered AI in Consumer Electronics, Proceedings",
pages = "525--526",
booktitle = "ICCE-TW 2026 - The 13th IEEE International Conference on Consumer Electronics - Taiwan",
}