In some instances, the disclosure provides a method for identifying access anomalies using network graphs. The method comprises obtaining access data for an entity, generating a network graph baseline profile based on the plurality of data elements, generating a network graph current profile based on the plurality of data elements, generating comparison data based on comparing the plurality of baseline network graphs with the one or more current network graphs and comparing the plurality of baseline nodes and the plurality of baseline edges with the plurality of current nodes and the plurality of current edges, determining, based on the comparison data, anomaly data comprising one or more flagged network accesses to the enterprise system, and providing the anomaly data indicating the flagged network accesses to an authentication system.

A transmitting data between a real first network and a real second network is provided. The transmission device has a first network port for coupling to the real first network and a second network port for coupling to the real second network and also comprises: a simulation unit which is connected to the first network port and which is configured to receive network-specific data from the real first network via the first network port, to provide, in accordance with the received network-specific data, a virtual simulation network of the real first network, and to prepare the provided virtual simulation network, via the second network port, for access to the provided virtual simulation network by the real second network. The transmission device provided allows an attacker to be deliberately deceived, which increases security against attempts to access the real first network from the real second network.

A method includes partitioning a set of configuration management (CM) data for one or more cellular network devices into multiple distinct time intervals, each time interval associated with a distinct set of CM settings at the one or more cellular network devices, the CM data comprising multiple CM parameters. The method also includes determining a regression model based on the set of CM data. The method also includes applying the regression model to compute a distinct set of scores and compare the set of scores to estimate whether a performance of the one or more cellular network devices has changed during a second time interval relative to a first time interval.

A method to provision a node network including provisioning a first generation of nodes by a root node; and provisioning a second generation of nodes by the first generation of nodes. Wherein at least one node from the first generation of nodes or the second generation of nodes is provisioned simultaneously with at least one other node from the first generation of nodes or the second generation of nodes.

A master node, a local node, a service assurance system, and a respective method performed thereby for predicting one or more metrics associated with a communication network are provided. The method performed by the master node operable in the communication network comprises receiving prediction(s) based on training data from local nodes in the communication network; and determining weight parameter(s) associated with the local nodes based on the current received prediction(s) and past received predictions. The method further comprises adjusting a respective local reporting policy for one or more local nodes based on the determined weight parameter(s).

In one embodiment, a label stability analyzer service receives classification data indicative of device type labels assigned to endpoints in a network by a device classification service. The label stability analyzer service counts device type label changes made by the device classification service to the endpoints. The label stability analyzer service computes variability metrics for the device type labels, wherein the variability metric for a device type label is based on a count of the device type label changes associated with that label. The label stability analyzer service determines, based on one of the variability metrics for a particular one of the device type labels exceeding a threshold value, a configuration change for the device classification service that adjusts how the device classification service applies the particular label to endpoints. The label stability analyzer service provides the configuration change to the device classification service.

A method for mapping underground sensors onto a network map may include obtaining a plurality of magnetic measurements from a plurality of sensors. The method may include using the plurality of magnetic measurements for determining a plurality of sensor locations in an initial network map. The method may include generating updated network maps from the perspective of each localized sensor. The method may include merging the updated network maps into a final network map, the final network map comprising a most accurate location for each sensor. The method may include determining inner localized sensors out of the plurality of sensors in the final network map. The method may include identifying the inner localized sensors as new base station anchors. The method may include mapping the inner localized sensors onto the final network map as new base station anchors.

Methods, systems and devices for network congestion control exploit the inherent burstiness of network traffic, using a wave-based characterization of network traffic and corresponding multiplexing methods and approaches.

A digital data communications network that supports efficient, scalable routing of data and use of network resources by combining a recursive division of the network into hierarchical sub-networks with repeating parameterized general purpose link communication protocols and an addressing methodology that reflects the physical structure of the underlying network hardware. The sub-division of the network enhances security by reducing the amount of the network visible to an attack and by insulating the network hardware itself from attack. The fixed bandwidth range at each sub-network level allows quality of service to be assured and controlled. The routing of data is aided by a topological addressing scheme that allows data packets to be forwarded towards their destination based on only local knowledge of the network structure, with automatic support for mobility and multicasting. The repeating structures in the network greatly simplify network management and reduce the effort to engineer new network capabilities.

The present disclosure relates to a communication system based on a neural network model, and a configuration method therefor. The communication system includes at least one master node and multiple child nodes that are in communication connection with the master node, and a child node neural network model is configured in each of the multiple child nodes. The configuration method for the communication system includes: obtaining feature information of the multiple child nodes; and dynamically configuring the child node neural network models on the basis of the obtained feature information.