DALHOUSIE NIMS LAB ATTACK DATASET 2025-1
收藏IEEE2026-04-17 收录
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https://ieee-dataport.org/documents/dalhousie-nims-lab-attack-dataset-2025-1
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资源简介:
DALHOUSIE NIMS LAB ATTACK IOT DATASET 2025-1 dataset comprises of four prevalent types attacks, namely Portscan, Slowloris, Synflood, and Vulnerability Scan, on nine distinct Internet of Things (IoT) devices. These attacks are very common on the IoT eco-systems because they often serve as precursors to more sophisticated attack vectors. By analyzing attack vector traffic characteristics and IoT device responses, our dataset will aid to shed light on IoT eco-system vulnerabilities. A Raspberry Pi was utilized to launch the attacks, targetting the devices in a controlled environment and each attack lasted 50 minutes.
提供机构:
Adjei, Jeffrey Attakorah; Nandy, Biswajit; Seddigh, Nabil; Heywood, Malcom; Zincir-Heywood, Nur



