Abstract: Techniques are described herein for implementing and using a secure access service edge (SASE) exchange system to allow SASE providers to share SASE services with other providers. A SASE exchange system may be used by any number of SASE providers to support SASE roaming by user endpoints between different SASE providers. A user endpoint may use SASE roaming to access additional sets of SASE services and capabilities that cannot be provided by a home SASE provider and/or other current SASE provider(s) of the user endpoint. In some examples, a SASE exchange system may be used to transition user endpoints from one SASE provider to another. Additionally or alternatively, the SASE exchange system may determine a combination of SASE providers that can be used to provide different subsets of shared SASE services/capabilities to a user endpoint.

Abstract: Techniques are described herein for implementing and using a secure access service edge (SASE) exchange system to allow SASE providers to share SASE services with other providers. A SASE exchange system may be used by any number of SASE providers to support SASE roaming by user endpoints between different SASE providers. A user endpoint may use SASE roaming to access additional sets of SASE services and capabilities that cannot be provided by a home SASE provider and/or other current SASE provider(s) of the user endpoint. In some examples, a SASE exchange system may be used to transition user endpoints from one SASE provider to another. Additionally or alternatively, the SASE exchange system may determine a combination of SASE providers that can be used to provide different subsets of shared SASE services/capabilities to a user endpoint.

Abstract: A system and method are provided that use an intelligence model that continuously learns and identifies changes within a production computing environment and determines if adjustments/changes to be made in the production computing environment are to be validated during testing based on a set of criteria. The intelligence model determines possible adjustments in a computing environment (and their impact during testing) that have been learned from stored/accumulated data associated with a plurality of production computing environments over time.

Abstract: A method comprises: receiving a query on a topic from a user associated with user attributes indicative of a user comprehension level on the topic; providing the query to an AI model; receiving from the AI model a response to the query that has a response comprehension level on the topic that is less than the user comprehension level; iteratively adding, to the query, topically-relevant user attributes of the user attributes to produce iterative queries that increase in technical detail on the topic; providing the iterative queries to the AI model; responsive to providing the iterative queries, receiving, from the AI model, iterative responses that increase in technical detail on the topic and have response comprehension levels that increase on the topic; and determining, among the iterative responses, a final response having a response comprehension level that most nearly matches the user comprehension level.

Abstract: A method includes creating, via a server, a plurality of virtualized human personalities associated with respective human users; receiving, via the server, a cyberattack message; determining, via the server, the cyberattack message targets a human user of the respective human users; selecting, via the server, a virtualized human personality of the plurality of virtualized human personalities based on the virtualized human personality being associated with the human user targeted by the cyberattack message; and responding, via the server, to the cyberattack message using the virtualized human personality selected from the plurality of virtualized human personalities.

Abstract: Techniques for associating manufacturer usage description (MUD) security profiles for Internet-of-Things (IoT) device(s) with secure access service edge (SASE) solutions, providing for automated and scalable integration of IoT devices with SASE frameworks. A MUD controller may utilize a MUD uniform resource identifier (URI) emitted by an IoT device to fetch an associated MUD file from a MUD file server associated with a manufacturer of the IoT device. The MUD controller may determine that a security recommendation included in the MUD file is to be implemented by a cloud-based security service provided by the SASE service and cause the IoT device to establish a connection with a secure internet gateway associated with the cloud-based security service. Additionally, or alternatively, the MUD file may include SASE extensions indicating manufacturer recommended cloud-based security services. Further, cloud-based security services may be implemented if local services are unavailable.

Abstract: Devices and methods are discussed herein to track networked electronic devices during the course of their lifecycles. Each electronic device may be provided with a “green passport” by its manufacturer which contains all relevant information concerning the operation of the device during its lifetime. When a new electronic device is coupled to a network, it may emit a uniform resource identifier (URI) which may be received by a server that may operate as a manager for the green passports of devices within its purview. The manager may download the green passport from the manufacturer's server. The manager may verify the authenticity of the URI and/or the green passport to avoid security threats. The manager may monitor the electronic device and issue notifications throughout its lifecycle. At the end-of-life of the electronic device, the manager may issue sustainable disposable information for the device.

Abstract: A system and method for an artificial intelligence (AI) confidentiality proxy that can protect a network from the transferal of sensitive AI data sets to outside AI systems. A data contract is established between the proxy and outside AI systems could function as well as user personas for additional protection. This system can also integrate with the network and provide security policy content and inspection rules.

Abstract: Techniques described herein relate to automatically generating standard network device configurations. In one example, one or more groups of network device configuration blocks may be obtained. An analysis of the one or more groups of network device configuration blocks may be performed, including identifying respective frequencies associated with respective network device configuration blocks of the one or more groups of network device configuration blocks. Based on the respective frequencies, one or more network device configuration blocks of the one or more groups of network device configuration blocks may be automatically aggregated into a standard network device configuration.

Abstract: In one embodiment, a device including a processor, and a memory to store data used by the processor, wherein the processor is operative to run a manufacturer usage description (MUD) controller operative to obtain a MUD profile of an Internet of Things (IoT) device from a MUD server, the MUD profile of the IoT device including: access rights of the IoT device, and any one or more of the following a default device username and/or a default device password of the IoT device, a recommended/required device password complexity of the IoT device, at least one service that should be enabled/disabled on the IoT device, and/or allowed security protocols and/or ciphers for communication to and/or from the IoT device, enforce security of the IoT device according to the MUD profile of the IoT device. Related apparatus and methods are also described.

Abstract: A packet capture operation is configured via a first computing device. The packet capture operation is configured to capture packets provided by a second computing device. The first computing device obtains an indication that a user is within a predetermined location proximity to the second computing device. The packet capture operation is initiated in response to obtaining the indication at the first computing device.

Abstract: A packet capture operation is configured via a first computing device. The packet capture operation is configured to capture packets provided by a second computing device. The first computing device obtains an indication that a user is within a predetermined location proximity to the second computing device. The packet capture operation is initiated in response to obtaining the indication at the first computing device.

Abstract: Techniques for a network controller associated with a firewall service to determine a network policy based on operational tolerances associated with a device, and cause the network policy to be provisioned at the firewall service where control commands, such as, for example, supervisory control and data acquisition (SCADA) commands, may be allowed or denied transmission to the device based on the operational tolerance(s) associated with the device. In some examples, the network controller may be configured as a manufacturer usage description (MUD) controller configured to transmit a MUD uniform resource identifier (URI), emitted by the device, to a MUD file server associated with the manufacturer of the device. The MUD file may be enhanced to include the operational tolerances associated with the device and transmitted back to the MUD controller where it may be parsed to determine a corresponding network policy.

Abstract: Techniques for a context-aware secure access service edge (SASE) engine for generating security profile(s) associated with endpoint device(s) accessing the network and using the security profile(s) to evaluate a traffic flow from the endpoint device(s). The SASE engine may execute on an edge device of a computing resource network and may be configured to maintain a security profile database including an endpoint security profile mapping. Endpoint device(s) accessing the network may share endpoint, application, and/or user specific information with the SASE engine so that the SASE engine may generate a security profile specific to the endpoint, application, and/or user. Additionally, an enterprise network, associated with endpoint device(s) accessing the network, may provide default SASE security profile templates to the SASE engine.

Abstract: Techniques for associating manufacturer usage description (MUD) security profiles for Internet-of-Things (IoT) device(s) with secure access service edge (SASE) solutions, providing for automated and scalable integration of IoT devices with SASE frameworks. A MUD controller may utilize a MUD uniform resource identifier (URI) emitted by an IoT device to fetch an associated MUD file from a MUD file server associated with a manufacturer of the IoT device. The MUD controller may determine that a security recommendation included in the MUD file is to be implemented by a cloud-based security service provided by the SASE service and cause the IoT device to establish a connection with a secure internet gateway associated with the cloud-based security service. Additionally, or alternatively, the MUD file may include SASE extensions indicating manufacturer recommended cloud-based security services. Further, cloud-based security services may be implemented if local services are unavailable.

Abstract: Techniques are described herein for implementing and using a secure access service edge (SASE) exchange system to allow SASE providers to share SASE services with other providers. A SASE exchange system may be used by any number of SASE providers to support SASE roaming by user endpoints between different SASE providers. A user endpoint may use SASE roaming to access additional sets of SASE services and capabilities that cannot be provided by a home SASE provider and/or other current SASE provider(s) of the user endpoint. In some examples, a SASE exchange system may be used to transition user endpoints from one SASE provider to another. Additionally or alternatively, the SASE exchange system may determine a combination of SASE providers that can be used to provide different subsets of shared SASE services/capabilities to a user endpoint.

Abstract: Techniques for associating manufacturer usage description (MUD) security profiles for Internet-of-Things (IoT) device(s) with secure access service edge (SASE) solutions, providing for automated and scalable integration of IoT devices with SASE frameworks. A MUD controller may utilize a MUD uniform resource identifier (URI) emitted by an IoT device to fetch an associated MUD file from a MUD file server associated with a manufacturer of the IoT device. The MUD controller may determine that a security recommendation included in the MUD file is to be implemented by a cloud-based security service provided by the SASE service and cause the IoT device to establish a connection with a secure internet gateway associated with the cloud-based security service. Additionally, or alternatively, the MUD file may include SASE extensions indicating manufacturer recommended cloud-based security services. Further, cloud-based security services may be implemented if local services are unavailable.

Abstract: This disclosure describes techniques for selectively providing access to a physical space. An example method includes identifying a location of a device associated with an authorized user based on an electromagnetic signal received by at least one sensor from the device. The electromagnetic signal has a frequency that is greater than or equal to 24 gigahertz (GHz). The example method further includes determining that the location of the device is within a threshold distance of a location of a threshold to a secured space and determining that an authentication score indicating that an individual carrying the device is the authorized user is greater than a threshold score. The authentication score is associated with multiple authentication factors identified by the device. Based on determining that the authentication score is greater than the threshold score, the threshold is unlocked and/or opened.

Abstract: Techniques for orchestrating a machine learning (ML) system on a distributed network. Determined performance levels for a ML system, determined from performance data received from the distributed network, are compared to performance requirements from the ML system. An orchestration module for the ML system then determines adjustments for the ML system that will improve the performance of the ML system and executes the adjustments for the ML system.

Abstract: In one embodiment, a device including a processor, and a memory to store data used by the processor, wherein the processor is operative to run a manufacturer usage description (MUD) controller operative to obtain a MUD profile of an Internet of Things (IoT) device from a MUD server, the MUD profile of the IoT device including: access rights of the IoT device, and any one or more of the following a default device username and/or a default device password of the IoT device, a recommended/required device password complexity of the IoT device, at least one service that should be enabled/disabled on the IoT device, and/or allowed security protocols and/or ciphers for communication to and/or from the IoT device, enforce security of the IoT device according to the MUD profile of the IoT device. Related apparatus and methods are also described.