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Botnet Attack Detection Approach in IoT Networks

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Abstract

An approach to detecting network attacks based on deep learning (autoencoders) is proposed. It is shown that learning examples can be obtained by connecting IoT devices to the network, as long as the traffic does not carry malicious code. Statistical values and functions extracted from traffic are proposed; patterns of IoT devices are based on them.

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