Abstract: According to some embodiments, a system, method and non-transitory computer-readable medium are provided to protect a cyber-physical system having a plurality of monitoring nodes comprising: a normal space data source storing, for each of the plurality of monitoring nodes, a series of normal monitoring node values over time that represent normal operation of the cyber-physical system; a situational awareness module including an abnormal data generation platform, wherein the abnormal data generation platform is operative to generate abnormal data to represent abnormal operation of the cyber-physical system using values in the normal space data source and a generative model; a memory for storing program instructions; and a situational awareness processor, coupled to the memory, and in communication with the situational awareness module and operative to execute the program instructions to: receive a data signal, wherein the received data signal is an aggregation of data signals received from one or more of the p

Abstract: According to some embodiments, a system, method and non-transitory computer-readable medium are provided to protect a cyber-physical system having a plurality of monitoring nodes comprising: a normal space data source storing, for each of the plurality of monitoring nodes, a series of normal monitoring node values over time that represent normal operation of the cyber-physical system; a situational awareness module including an abnormal data generation platform, wherein the abnormal data generation platform is operative to generate abnormal data to represent abnormal operation of the cyber-physical system using values in the normal space data source and a generative model; a memory for storing program instructions; and a situational awareness processor, coupled to the memory, and in communication with the situational awareness module and operative to execute the program instructions to: receive a data signal, wherein the received data signal is an aggregation of data signals received from one or more of the p

Abstract: Methods and systems for self-certifying secure operation of a cyber-physical system having a plurality of monitoring nodes. In an embodiment, an artificial intelligence (AI) watchdog computer platform obtains, using the output of a local features extraction process of time series data of a plurality of monitoring nodes of a cyber-physical system and a global features extraction process, global features extraction data. The AI watchdog computer platform then obtains reduced dimensional data, generates an updated decision boundary, compares the updated decision boundary to a certification manifold, determines based on the comparison that the updated decision boundary is certified, and determines, based on an anomaly detection process, whether the cyber-physical system is behaving normally or abnormally.

Abstract: According to some embodiments, a system, method and non-transitory computer-readable medium are provided to protect a cyber-physical system having a plurality of monitoring nodes comprising: a normal space data source storing, for each of the plurality of monitoring nodes, a series of normal monitoring node values over time that represent normal operation of the cyber-physical system; a situational awareness module including an abnormal data generation platform, wherein the abnormal data generation platform is operative to generate abnormal data to represent abnormal operation of the cyber-physical system using values in the normal space data source and a generative model; a memory for storing program instructions; and a situational awareness processor, coupled to the memory, and in communication with the situational awareness module and operative to execute the program instructions to: receive a data signal, wherein the received data signal is an aggregation of data signals received from one or more of the p

Abstract: Methods and systems for self-certifying secure operation of a cyber-physical system having a plurality of monitoring nodes. In an embodiment, an artificial intelligence (AI) watchdog computer platform obtains, using the output of a local features extraction process of time series data of a plurality of monitoring nodes of a cyber-physical system and a global features extraction process, global features extraction data. The AI watchdog computer platform then obtains reduced dimensional data, generates an updated decision boundary, compares the updated decision boundary to a certification manifold, determines based on the comparison that the updated decision boundary is certified, and determines, based on an anomaly detection process, whether the cyber-physical system is behaving normally or abnormally.

Abstract: The description provides a signal detection system employing a wireless, passive detection device that utilizes waveform shifting for reporting signals to a reader device. The system is useful for a variety of applications including as an implanted medical device for monitoring patient conditions.