Abstract: A network sensor, inserted into a mirror port of a network switch or router, may be configured to monitor the network traffic originating from an embedded device. Metadata in the network traffic may be passively extracted by the network sensor and transmitted to a server in order to monitor and analyze the behavior of the embedded device. The server may employ machine learning to distinguish typical behavior of the embedded device from atypical behavior. Further, code may be injected into the firmware of the embedded device, and the code may be programmed to broadcast a performance beacon whenever certain firmware functions are executed. A collection of the performance beacons may be analyzed at the server to reconstruct an execution path of the embedded device, and machine learning may be applied to determine whether the execution path is typical or atypical.

Abstract: A network sensor, inserted into a mirror port of a network switch or router, may be configured to monitor the network traffic originating from an embedded device. Metadata in the network traffic may be passively extracted by the network sensor and transmitted to a server in order to monitor and analyze the behavior of the embedded device. The server may employ machine learning to distinguish typical behavior of the embedded device from atypical behavior. Further, code may be injected into the firmware of the embedded device, and the code may be programmed to broadcast a performance beacon whenever certain firmware functions are executed. A collection of the performance beacons may be analyzed at the server to reconstruct an execution path of the embedded device, and machine learning may be applied to determine whether the execution path is typical or atypical.