Content selection associated with webview browsers

    公开(公告)号:US11748777B1

    公开(公告)日:2023-09-05

    申请号:US17396115

    申请日:2021-08-06

    申请人: Google LLC

    发明人: Gang Wang Yong Yao

    摘要: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium for delivering content. A method includes: identifying a webview; providing a script for execution when the webview is initiated, the script causing a device associated with the webview to retrieve a unique identifier associated with the device, encode the unique identifier, construct a URL that includes an advertising system domain and the encoded unique identifier, and pass the encoded unique identifier to the advertising system; passing a cookie for the advertising domain back to the webview for inclusion in the cookie space of the webview; storing information related to interactions of a user of the device when accessing content through different browsers or applications so as to unify the cookie spaces of the different browsers; identifying a request for content as being associated with the device; and using the information to determine content for delivery.

    THIRD PARTY CUSTOMIZED CONTENT BASED ON FIRST PARTY

    公开(公告)号:US20230237537A1

    公开(公告)日:2023-07-27

    申请号:US18192869

    申请日:2023-03-30

    申请人: Google LLC

    发明人: Gang Wang Yong Yao

    IPC分类号: G06Q30/0241 G06F21/62

    摘要: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium for providing content. A method includes: receiving a first request for filling a slot on a first publisher page, the request including an encrypted publisher cookie; providing content responsive to the request; upon receipt of an indication that a user interacted with the content, creating and providing a content serving system cookie; linking the received encrypted publisher cookie with the content serving system cookie; receiving a second, different request for content in association with rendering a second, different publisher page, the second, different request including an encrypted publisher cookie associated with the second different publisher page and the previously provided content serving system cookie; linking the received encrypted publisher cookie associated with the second, different publisher page with the encrypted publisher cookie associated with the first publisher page; and using the linkings to determine content to deliver.

    SECURELY DETECTING ONLINE FRAUD MALWARE
    94.
    发明公开

    公开(公告)号:US20230199021A1

    公开(公告)日:2023-06-22

    申请号:US17925521

    申请日:2020-09-30

    申请人: Google LLC

    IPC分类号: H04L9/40 H04L9/32

    摘要: A method for secure detection of online fraud. The method includes generating an encrypted profile representing browser activity, sending the encrypted profile to a secure multiparty computation system, receiving a trust token from the secure multiparty computation system, based on a determination that the web browser is not engaged in online fraud, sending a request to redeem the trust token with the secure multiparty computation system, receiving an encrypted record of redemption from the secure multiparty computation system based on a determination that a web site associated with the web content is not blocked, and sending a request, containing the encrypted record of redemption, for third-party content, wherein the third-party content is associated with the web content.

    USING SECURE MULTI-PARTY COMPUTATION AND PROBABILISTIC DATA STRUCTURES TO PROTECT ACCESS TO INFORMATION

    公开(公告)号:US20230188329A1

    公开(公告)日:2023-06-15

    申请号:US17924561

    申请日:2021-12-13

    申请人: Google LLC

    IPC分类号: H04L9/08 G06F16/28 G06F21/62

    摘要: This document describes systems and techniques for protecting the security of information in content selection and distribution. In one aspect, a method includes receiving, by a first computing system of MPC systems, a digital component request including distributed point functions that represent a secret share of a respective point function that indicates whether a user of the client device is a member of a first user group. Selection values are identified. Each selection value corresponds to a respective digital component, a set of contextual signals, and a respective second user group identifier for a respective second user group to which the respective digital component is eligible to be distributed. A determination is made, for each selection value and using the distributed point functions in a secure MPC process, a candidate parameter that indicates whether the second user group identifier matches a user group that includes the user as a member.

    FEEDBACK CONTROLLER USING SECRET SHARING

    公开(公告)号:US20230077152A1

    公开(公告)日:2023-03-09

    申请号:US17795151

    申请日:2021-12-13

    申请人: Google LLC

    IPC分类号: G06Q30/02

    摘要: This document describes to pacing digital component distribution and controlling the use of digital component distribution rate using feedback controllers implemented using secret sharing. In one aspect, a method includes, for each of one or more campaigns, initializing by a first computing system of multi-party computation (MPC) systems and in collaboration with one or more NI second computing systems of the MPC systems, a feedback controller for the campaign in secret shares using a secure MPC process. The first computing system updates, a first secret share of an output of the feedback controller based on an error parameter representing a difference between a setpoint and a measured rate for the campaign. The first computing system determines, based at least on the first secret share of the output, a first secret share of a pacing selector parameter that defines whether the campaign satisfies a pacing eligibility condition for the campaign.

    USING SECURE MPC AND VECTOR COMPUTATIONS TO PROTECT ACCESS TO INFORMATION IN CONTENT DISTRIBUTION

    公开(公告)号:US20230076256A1

    公开(公告)日:2023-03-09

    申请号:US17793831

    申请日:2022-01-06

    申请人: Google LLC

    IPC分类号: H04L9/08 G06F21/62

    摘要: This disclosure relates to protecting the security of information in content selection and distribution. In one aspect, a method includes receiving, from a client device and by a first computing system of multi-party computation (MPC) systems, a digital component request including first secret shares of data identifying user groups that include a user of the client device as a member. The first computing system transmits a contextual digital component request to a content platform. The first computing system receives, from the content platform, selection data for multiple digital components. The selection data includes first vector data defining a contextual-based vector of values selected based in part on the set of contextual signals. The first computing system obtains, for each digital component, second vector data defining a user group-based vector of values selected based in part on a respective user group corresponding to the digital component.

    TAMPER-PROOF INTERACTION DATA
    98.
    发明申请

    公开(公告)号:US20230073437A1

    公开(公告)日:2023-03-09

    申请号:US17419604

    申请日:2020-05-22

    申请人: Google LLC

    摘要: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for validating interactions with false rendered elements. In one aspect, a method includes receiving a rendering notification and a declaration of a rendered element defined in an active window on a client device, detecting interaction with the rendered element at the client device, determining whether the interaction occurred at a declared location of the rendered element within the active window, and processing the interaction including: in response to determining that the interaction occurred: capturing a screenshot of the active window on the client device; verifying a visual appearance of the rendered element in the screenshot with a declared appearance of the rendered element, and generating an interaction attestation, thereby validating the interaction. In response to determining that the interaction did not occur, refraining from generating the interaction attestation.

    PRIVACY-PRESERVING TECHNIQUES FOR CONTENT SELECTION AND DISTRIBUTION

    公开(公告)号:US20230072957A1

    公开(公告)日:2023-03-09

    申请号:US17794146

    申请日:2021-12-10

    申请人: Google LLC

    IPC分类号: H04L9/40 G06F21/62

    摘要: This document describes systems and techniques for improving the integrity and protecting the security of information in content selection and distribution. In one aspect, a method includes receiving, by a first server of a secure multi-party computation (MPC) system and from an application on a client device, a request for a selection value. In response to receiving the request, the first server conducts, in collaboration with a second server of the secure MPC system, a privacy-preserving selection process and a counterfactual selection process. The first server transmits a selection result defining the first winning selection value from the privacy-preserving selection process and the second winning selection value from the counterfactual selection process and receives, from the application on the client device, a notification indicating that a digital component corresponding to the winning selection value from the privacy-preserving selection process was presented at the client device.

    BOOSTING AND MATRIX FACTORIZATION
    100.
    发明申请

    公开(公告)号:US20230050538A1

    公开(公告)日:2023-02-16

    申请号:US17773650

    申请日:2021-03-26

    申请人: Google LLC

    发明人: Gang Wang Pengyu He

    IPC分类号: G06K9/62 G06N20/00

    摘要: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for presenting a new machine learning model architecture. In some aspects, the methods include obtaining a training dataset with a plurality of training samples that includes feature variables and output variables. A first matrix is generated using the training dataset which is a sparse representation of the training dataset. Generating the first matrix can include generating a categorical representation of numeric features and an encoded representation of the categorical features. The methods further include generating a second, third and a fourth matrix. Each feature of the first matrix is then represented using a vector that includes a multiple adjustable parameters. The machine learning model can learn by adjusting values of the adjustable parameters using a combination of a loss function the fourth matrix, and the first matrix.