Abstract: An electrical distribution system includes a plurality of electrical substations. Each of the electrical substations includes a plurality of intelligent electronic devices (IEDs), and a communications network interconnecting the plurality of IEDs at that substation. The communications networks at the plurality of substations are configured as at least one virtual network spanning multiple ones of the plurality of electrical substations, and interconnecting at least some of the IEDs within the multiple ones of the plurality of electrical substations, and so that delays experience by messages on the at least one virtual network are below a defined threshold. The virtual networks may be reconfigured when/if the threshold is not met.

Abstract: A system for obtaining information about an Internet of Things (IoT) device connected to a network includes a data traffic collection point, a data processing module and an artificial intelligence module. The data traffic collection point collects data units communicated to or from a specified IoT device of a plurality of IoT devices connected to a network. The data processing module processes quantitative information pertaining to the data units communicated to or from the specified IoT device collected over a defined time interval, to create a temporal data traffic fingerprint of the specified IoT device. The artificial intelligence module utilizes a machine learning model to deduce device identifying information of the specified IoT device from the temporal data traffic fingerprint of the specified IoT device.

Abstract: A system for obtaining information about an Internet of Things (IoT) device connected to a network includes a data traffic collection point, a data processing module and an artificial intelligence module. The data traffic collection point collects data units communicated to or from a specified IoT device of a plurality of IoT devices connected to a network. The data processing module processes quantitative information pertaining to the data units communicated to or from the specified IoT device collected over a defined time interval, to create a temporal data traffic fingerprint of the specified IoT device. The artificial intelligence module utilizes a machine learning model to deduce device identifying information of the specified IoT device from the temporal data traffic fingerprint of the specified IoT device.

Abstract: Examples of techniques for event prediction in a control communication network are disclosed. Aspects include determining state data associated with one or more devices associated with a control communication network, generating, by a machine learning model, a feature vector comprising a plurality of features extracted from the state data, and determining one or more event predictions associated with the control communication network based at least in part on the feature vector.

Abstract: An electrical distribution system includes a plurality of electrical substations. Each of the electrical substations includes a plurality of intelligent electronic devices (IEDs), and a communications network interconnecting the plurality of IEDs at that substation. The communications networks at the plurality of substations are configured as at least one virtual network spanning multiple ones of the plurality of electrical substations, and interconnecting at least some of the IEDs within the multiple ones of the plurality of electrical substations, and so that delays experience by messages on the at least one virtual network are below a defined threshold. The virtual networks may be reconfigured when/if the threshold is not met.