Machine learning in IoT analyzes data patterns to detect anomalies and predict potential security breaches.
What are the challenges in securing IoT devices used in remote healthcare monitoring?
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Machine learning in IoT analyzes data patterns to detect anomalies and predict potential security breaches.
Machine learning in IoT involves the use of algorithms to analyze data patterns, detect anomalies, and predict potential security breaches within interconnected devices and systems. By continuously monitoring and analyzing data from sensors and devices, machine learning models can identify unusual patterns or activities that may indicate a security threat. This proactive approach helps in strengthening the security of IoT networks and minimizing the risks associated with potential breaches.