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Article summary:

1. IoT architecture: The article introduces a three-layer IoT architecture consisting of the thing layer, fog layer, and cloud layer, which enables data collection and processing from various IoT devices with limited resources.

2. Machine learning for IoT security: The article discusses the use of machine learning algorithms for detecting IoT attacks, highlighting the limitations of traditional ML techniques in real-time predictions and low-resource environments.

3. Ensemble model for IoT attack detection: The article proposes an ensemble model for detecting IoT attacks that does not require additional feature extraction or dimensional reduction algorithms and is best suited for real-time applications with limited resources. Extensive experiments on the NSL-KDD dataset show high accuracy in minimum time with fewest possible resources needed.

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