CLASSIFICATION-BASED DATA PRIVACY AND SECURITY MANAGEMENT

    公开(公告)号:US20240056488A1

    公开(公告)日:2024-02-15

    申请号:US17886030

    申请日:2022-08-11

    CPC classification number: H04L63/205 H04L63/0478

    Abstract: Techniques are described for classification-based data security management. The classification-based data security management can include utilizing device and/or data attributes to identify security modes for communication of data stored in a source device. The security modes can be identified based on a hybrid-encryption negotiation. The attributes can include a device resource availability value, an access trust score, a data confidentiality score, a geo-coordinates value, and/or a date/time value. The security modes can include a hybrid-encryption mode. The source device can utilize the hybrid-encryption mode to transmit the data, via one or more network nodes, such as an edge node, to one or more service nodes.

    Context-based security policy for data access and visibility

    公开(公告)号:US11818137B2

    公开(公告)日:2023-11-14

    申请号:US17490004

    申请日:2021-09-30

    CPC classification number: H04L63/104 G06V40/173 H04L63/20

    Abstract: A method, computer system, and computer program product are provided for controlling data access and visibility using a context-based security policy. A request from an endpoint device to receive data is received at a server, wherein the request includes one or more contextual attributes of the endpoint device including an identity of a user of the endpoint device. The one or more contextual attributes are processed to determine that the endpoint device is authorized to receive the data. A security policy is determined for the data based on the one or more contextual attributes. The data is transmitted, including the security policy, to the endpoint device, wherein the endpoint devices enforces the security policy to selectively permit access to the data by preventing the endpoint device from displaying the data to an unauthorized individual.

    Drift detection for predictive network models

    公开(公告)号:US11722359B2

    公开(公告)日:2023-08-08

    申请号:US17479297

    申请日:2021-09-20

    CPC classification number: H04L41/064 G06F18/214 H04L41/16 H04L43/04

    Abstract: A method, computer system, and computer program product are provided for detecting drift in predictive models for network devices and traffic. A plurality of streams of time-series telemetry data are obtained, the time-series telemetry data generated by network devices of a data network. The plurality of streams are analyzed to identify a subset of streams, wherein each stream of the subset of streams includes telemetry data that is substantially empirically distributed. The subset of streams of time-series data are analyzed to identify a change point. In response to identifying the change point, additional time-series data is obtained from one or more streams of the plurality of streams of time-series telemetry data. A predictive model is trained using the additional time-series data to update the predictive model and provide a trained predictive model.

    Microservice visibility and control

    公开(公告)号:US11601393B1

    公开(公告)日:2023-03-07

    申请号:US17493099

    申请日:2021-10-04

    Abstract: Methods are provided in which a domain name system (DNS) service obtains a lookup request for information about a source of a traffic flow being transmitted to a network resource external of a service cluster and performs, based on the lookup request, a lookup operation for a microservice that is the source of the traffic flow, among a plurality of microservices of the service cluster registered with the DNS service. The methods further include providing information about the microservice based on the lookup operation. The information includes at least a name of the microservice for visibility of the microservice external of the service cluster.

    Switch triggered traffic tracking
    39.
    发明授权

    公开(公告)号:US11509532B2

    公开(公告)日:2022-11-22

    申请号:US17021265

    申请日:2020-09-15

    Abstract: Systems and methods provide for performing performance analytics processing of network traffic by copying packets of network traffic to a switch CPU based on a flag. The systems and methods disclosing receiving network traffic comprising one or more packet, generating a network traffic flow record associated with the received network traffic, the network traffic flow record including a copy-to-CPU bit and one or more function flag bits, setting the copy-to-CPU bit to an on configuration, processing the one or more packets by one or more functions to generate network flow analytics, wherein the one or more function flag bits are set in response to the one or more functions generating network flow analytics, and setting the copy-to-CPU bit to an off configuration.

    PEER RISK BENCHMARKING USING GENERATIVE ADVERSARIAL NETWORKS

    公开(公告)号:US20220131761A1

    公开(公告)日:2022-04-28

    申请号:US17077073

    申请日:2020-10-22

    Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

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