A cybersecurity scanner deployment system, comprising: at least one processor configured to: access a primary account maintained in a cloud environment; receive information defining a structure of the primary account, the structure including a plurality of assets, and the information excluding raw data of the primary account; deploy, inside the primary account or a secondary account for which trust is established with the primary account, at least one ephemeral scanner configured to scan at least one block storage volume and output metadata defining the at least one block storage volume, the output excluding raw data of the primary account; receive a transmission of the metadata from the at least one ephemeral scanner, excluding raw data of the primary account; analyze the metadata to identify cybersecurity vulnerabilities; correlate each of the cybersecurity vulnerabilities with one of the assets; and generate a report correlating the cybersecurity vulnerabilities with the assets.

According to one embodiment, a method, computer system, and computer program product for cloud service brokerage. The embodiment may include receiving a data set and user defined contextual parameters relating to a machine learning (ML) problem of a user to be performed on the data set. The embodiment may include identifying a resource requirement of the ML problem and available resources. The embodiment may include enabling user configuration of the contextual parameters in an interactive augmented reality (AR) view. The embodiment may include identifying a set of clusters upon which to execute computing tasks of the ML problem. The set of clusters is identified out of the available resources. The embodiment may include implementing a ML evaluation process to determine an optimized load distribution model for execution of the computing tasks within the set of clusters. The embodiment may include implementing the optimized load distribution model.

A method for transmitting a data packet from a central electronic computing device to a mobile terminal device using a network system involves transmitting the data packet to an electronic computing device of a motor vehicle of the network system using a mobile telecommunications network. The transmitted data packet is transmitted locally from the electronic computing device using a local network, which is created by the electronic computing device, to the at least one mobile terminal device.

Methods and systems for assessing internet exposure of a cloud-based workload are disclosed. A method comprises accessing at least one cloud provider API to determine a plurality of entities capable of routing traffic in a virtual cloud environment associated with a target account containing the workload, querying the at least one cloud provider API to determine at least one networking configuration of the entities, building a graph connecting the plurality of entities based on the networking configuration, accessing a data structure identifying services publicly accessible via the Internet and capable of serving as an internet proxy; integrating the identified services into the graph; traversing the graph to identify at least one source originating via the Internet and reaching the workload, and outputting a risk notification associated with the workload. Systems and computer-readable media implementing the above method are also disclosed.

Importing of a UE address into a VRF of perimeter equipment is facilitate by receiving a VPN update from the perimeter equipment including a route target of the perimeter equipment and a gNodeB address. In addition, session information is obtained by intercepting traffic between the UE address and a UPF. The session information including the UE address and address of a gNodeB to which the UE is connected. By matching the gNodeB addresses from the VPN update and the session information, the route target of the perimeter equipment to which the UE is connected may be determined. The UE address may then be imported exclusively into the VRF of the perimeter equipment.

Importing of a UE address into a VRF of perimeter equipment is facilitate by receiving a VPN update from the perimeter equipment including a route target of the perimeter equipment and a gNodeB address. In addition, session information is obtained by intercepting traffic between the UE address and a UPF. The session information including the UE address and address of a gNodeB to which the UE is connected. By matching the gNodeB addresses from the VPN update and the session information, the route target of the perimeter equipment to which the UE is connected may be determined. The UE address may then be imported exclusively into the VRF of the perimeter equipment.

In one embodiment, a device receives application experience metrics for a software-as-a-service application. The device generates, based on the application experience metrics, a predictive model that predicts application experience scores for a plurality of network service providers that provide connectivity to the software-as-a-service application. The device selects a particular network service provider for use by a location, based on an application experience score predicted by the predictive model. The device sends an indication of the particular network service provider to the location.

A data reporting method includes generating a data uploading token by a main network node, determining, from a plurality of data-uploading network nodes waiting for data uploading, a plurality of qualified network nodes having a data uploading qualification, allowing the qualified network nodes to compete for the data uploading token, and coordinating a data uploading operation with a winning network node of the qualified network nodes that obtained the data uploading token.

A data reporting method includes generating a data uploading token by a main network node, determining, from a plurality of data-uploading network nodes waiting for data uploading, a plurality of qualified network nodes having a data uploading qualification, allowing the qualified network nodes to compete for the data uploading token, and coordinating a data uploading operation with a winning network node of the qualified network nodes that obtained the data uploading token.

A real-time streaming service predicts an incoming flash crowd event and manages computing resources to respond to the event before traffic peaks, thus reducing the likelihood that the streaming service's resources will be overwhelmed. Embodiments of a real-time streaming server predict a flash crowd event by detecting actions by client devices during a multi-step process to access a real-time content stream from an endpoint server cluster. Initially, the endpoint server has first computing resources configured to stream the content stream to the client devices. The streaming server provisions second computing resources at the endpoint server based on a rate at which the client devices perform an action associated with a first step in the multi-step process. The second computing resources are configured to stream the real-time content stream based on a rate at which the client devices perform an action associated with a second step in the multi-step process.