Abstract: Methods and systems for continuously and quantitatively assessing the risk to data confidentiality, integrity, and availability on identified on endpoints, servers, medical devices, and “Internet of things” devices in a networked healthcare environment monitor resource requests by user applications running on the various device. A map of resource usage by each application may be generated. Based on the map and a risk model (e.g., the contents of a risk database), application events associated with risks are detected and resources vulnerable to the risk may be identified.

Abstract: Endpoint devices for use, e.g., in distributed environments such as a healthcare institutions comprise, in various embodiments, (i) a processor, (ii) an operating system, (iii) a computer memory, and (iv) instructions stored in the memory and executable by the processor for defining a plurality of user applications, a plurality of sensors for monitoring calls to the operating system, a plurality of actuators for causing the processor to take specified actions for mitigating a threat or anomaly, and an intelligent controller for analyzing time-windowed data from the sensors based on a predictive response model to detect anomalous behavior, and upon detecting such behavior, instructing an actuator to take a specified mitigation action.

Abstract: Methods and systems facilitate continuous processing of incoming data while one or more software components are updated and/or are temporarily unavailable. Computing tasks may be divided into idempotent steps with the computational state exchanged between steps saved in a persistent manner. In various embodiments, these steps are assembled into one or more computation pipelines.