Netskope, Inc.

Damian C Chung

James S Robinson

Lamont Orange

Robert Wayne Butler, Ii

Stevan W Pierce, Jr

Madhura Sridhar

A policy-controlled access security system for managing access security to electronic agents in cloud based multi-tenant systems includes a client device, a mid-link server, and a web server. A local application running on the client device requests access to an electronic agent of a remote application of the web server. Policies are determined for controlled access to the electronic agent. A token for the electronic agent is correlated with a plurality of tokens for identifying a user application associated with the token. The remote application is compared with the user application. A non-compliance of the set of policies is identified by determining enabling of one or more AI devices by the plurality of end users. The set of policies are modified based on the non-compliance and the functionality associated with the electronic agent and the plurality of privileges are updated for the end user based on the modified policies.

Artificial intelligence (AI) devices control based on policies

A video data loss prevention (vDLP) system that uses machine-learning for protection against data exfiltration of sensitive content across multiple tenants in a cloud-based network. The vDLP system consists of tenants that include end-user devices and a vDLP server. The vDLP server is configured to intercept traffic at an application layer of the cloud-based network and receive a video file from traffic. A viewer for the video file is remote from the cloud-based network. The vDLP server further recognizes text of audio and frames extracted from the video file using a machine-learning engine. The vDLP server then analyzes the frames and text using machine-learning classifiers, enforces policies against machine-learning classifiers for protection against data exfiltration of sensitive content in the video file, and sends a notification away from the cloud-based network upon detection of violation of a policy.

Video data loss prevention (vDLP)

A system uses an artificial intelligence (AI) engine to generate a response for end-user devices using services and to provide threat protection in a cloud-based network. The system consists of tenants, tunnels, the AI engine, and an AI reporter. A tenant includes the end-user devices. The tunnels transmit and segregate traffic between the end-user devices and the services. The AI engine intercepts traffic within tunnels, receives a request from a user, and determines a context. The AI engine further retrieves a user score for policy violations, analyzes the request, and applies functions to manage it. The context is built by analyzing interactions of users for similar requests. The AI engine generates the response based on the context and the user score and sends it to the user to fulfill the request. The AI reporter transmits information corresponding to the request and response across the tenants of the cloud-based network.

Middle-ware artificial intelligence (AI) engine

A policy-controlled authorization system including a local application on a client device, a policy component including a plurality of policies, and a mid-link server, coupled to the client device is provided. A request for access to a service using a token is provided by the local application. A correlator correlates the token with the plurality of tokens for identifying a policy from the plurality of policies associated with the token. A token inspector authorizes the token for accessing the service based on the correlation. Based on the authorization, either the token is authorized for access to the service via the remote application, or the token is blocked when unauthorized to prevent access to the service. Confidence scores are assigned to each token based on their categories, compliance with the policies, and a threat level. The confidence scores indicate need to re-authorize the tokens and/or disable them temporarily.

Policy-controlled token authorization

A policy-controlled access security system for managing access security to electronic agents in cloud based multi-tenant systems includes a client device, a mid-link server, and a web server. A local application running on the client device requests for access to an electronic agent of a remote application of the web server. Policies are determined corresponding to the electronic agent for controlled access to the electronic agent. A token for the electronic agent is correlated with a plurality of tokens for identifying a user application associated with the token. The remote application corresponding to the token from the request is compared with the user application. Based on the comparison an authorization is determined by the mid-link server corresponding to the token for accessing the electronic agent. The policies are enforced on the client device and the access to the electronic agent is provided based on the policies via the web server.

Electronic agent scribe and communication protections

A policy-controlled authorization system for managing tokens used to access services in a cloud based multi-tenant system. The policy-controlled authorization system includes a local application that executes on a client device, a policy component including a plurality of policies, and a mid-link server, coupled to the client device. A request for access to a service on a remote application running on a remote instance of a web server is provided by the local application. A token is required to access the service. A correlator correlates the token with the plurality of tokens for identifying a policy from the plurality of policies associated with the token. A token inspector authorizes the token for accessing the service based on the correlation. Based on the authorization, either the token is authorized for access to the service via the remote application, or the token is blocked when unauthorized to prevent access to the service.

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Gilbert, AZ, United States of America

Damian C Chung