IoT Flex Data
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IoT Flex Data数据集由科罗拉多州立大学创建,旨在通过模拟真实网络环境中的IoT活动,帮助提高物联网安全性。该数据集包含四种场景:IoT良性空闲、IoT良性活动、IoT设置和恶意攻击流量,涵盖了正常操作和攻击场景。数据集通过捕获实际IoT设备的网络流量,提供了1小时、5小时和10小时不间断的流量事件,便于研究人员在有限计算资源下进行分析。该数据集主要用于评估和改进物联网设备的安全性。
The IoT Flex Data dataset was developed by Colorado State University with the goal of simulating IoT activities in real network environments to bolster IoT security. The dataset encompasses four scenarios: IoT benign idle state, IoT benign activity, IoT setup, and malicious attack traffic, covering both normal operational and attack scenarios. It captures network traffic from actual IoT devices, offering uninterrupted traffic event datasets with durations of 1 hour, 5 hours, and 10 hours, enabling researchers to conduct analysis under constrained computing resources. This dataset is primarily utilized for evaluating and enhancing the security of IoT devices.

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