Controlled Network for IoT Cellular Security

The system segments the monitoring function into a dedicated Controlled Network layer that operates independently from the core cellular network. This segmentation allows the security monitoring to be implemented as a separate module that can be deployed without overloading the existing network infrastructure, thus improving threat detection while managing system complexity.

The patent introduces an intermediary Controlled Network (CN) that sits between the IoT devices and the core cellular network. This intermediary layer performs real-time monitoring and analysis of communication parameters, acting as a buffer that protects the core network from direct computational loads while maintaining security surveillance capabilities.

The system performs preliminary classification of IoT devices by type, functionality, and behavior patterns before monitoring their communications. This preliminary action creates device profiles and establishes baseline communication patterns, enabling the system to quickly identify deviations and threats without having to analyze every communication parameter from scratch, thus improving accuracy while reducing processing time.

The patent dynamically adjusts monitoring parameters and thresholds based on device classification and historical behavior data. By changing monitoring parameters adaptively rather than using fixed thresholds, the system achieves higher threat identification accuracy while processing fewer false positives, thereby reducing overall computational load and processing time.

The system implements a closed-loop feedback mechanism where detected security threats trigger automated response measures, and the results of these responses are fed back into the monitoring system. This feedback loop enables the Controlled Network to learn from past security incidents and refine its response strategies, improving protection effectiveness while automating the complexity of network interventions.

The patent enables the Controlled Network to automatically respond to security threats without requiring manual intervention for each incident. The system self-manages threat response by automatically classifying threats, selecting appropriate countermeasures, and executing them based on predefined security policies, thus improving protection effectiveness while reducing the operational complexity of network intervention.