Two-part context-based rendering solution for high-fidelity augmented reality in virtualized environment

    公开(公告)号:US10573057B1

    公开(公告)日:2020-02-25

    申请号:US16122461

    申请日:2018-09-05

    Abstract: Systems and methods for rendering an Augmented Reality (“AR”) object. The methods comprise: drawing a first bitmap of a first AR object rendered by a server on a display of a client device; selecting/focusing on a second AR object or a part of the first AR object shown on the display; communicating a request for the second AR object or the part of the first AR object from the client device to the server; obtaining, by the server, an object file for the second AR object or part of the first AR object; providing the object file to the client device; locally rendering, by the client device, the second AR object or part of the first AR object as a second bitmap; superimposing the second bitmap on the first bitmap to generate a third bitmap; and drawing the third bitmap on the display of the client device.

    SYSTEMS AND METHODS FOR DETECTING AND THWARTING ATTACKS ON AN IT ENVIRONMENT

    公开(公告)号:US20190260777A1

    公开(公告)日:2019-08-22

    申请号:US15900032

    申请日:2018-02-20

    Abstract: Systems and methods for detecting and thwarting attacks on a computing system. The methods comprise: collecting timestamped data from different software products comprising a unified end point management product, an SBC/ADV product, an application delivery controller product, a content collaboration product, and/or a software defined WAN product; analyzing the collected timestamped data to determine if an observed user behavior matches a learned normal user behavior of an authorized user associated with a user account; determining a risk classification level associated with a credential used by a user to log into the user account, when the observed user behavior does not match the learned normal user behavior of the authorized user; and causing at least one security related action to be performed when the risk classification level is greater than a threshold level or the risk classification level is one of a top N highest risk classification levels.

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