Machine learning detects anomalies in IoT networks by analyzing patterns and identifying deviations indicative of security breaches.
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Machine learning detects anomalies in IoT networks by analyzing patterns and identifying deviations indicative of security breaches.
Machine learning detects anomalies in IoT networks by analyzing patterns and identifying deviations indicative of security breaches. This process involves using algorithms to continuously monitor and analyze data from IoT devices, looking for unusual behaviors or patterns that deviate from normal operation. Upon detecting anomalies, the machine learning system can raise alerts or take corrective actions to mitigate potential security threats.