ANONYMOUS AUTHENTICATION WITH TOKEN REDEMPTION

    公开(公告)号:US20230308277A1

    公开(公告)日:2023-09-28

    申请号:US17924457

    申请日:2021-08-26

    Applicant: Google LLC

    CPC classification number: H04L9/3213 H04L9/3257

    Abstract: This disclosure relates to a method for anonymous attestation that includes receiving, by an application running on a client device and from a first content provider, an authentication request to authenticate a user to receive content from a second domain of a second content provider, redeeming, with an attestation token issuing system that issued an anonymous attestation token attesting to the user's authentication to the second content provider, the anonymous attestation token by transmitting the anonymous attestation token with a second request, receiving a redemption result representing whether the attestation token was successfully redeemed, signed by the attestation token issuing system using a digital signature and is operable to verify, to the second content provider, that the user is authenticated to the second content provider without identifying the user to the second content provider, and transmitting, to the first content provider, the redemption result.

    PROCESSING OF MACHINE LEARNING MODELING DATA TO IMPROVE ACCURACY OF CATEGORIZATION

    公开(公告)号:US20230274183A1

    公开(公告)日:2023-08-31

    申请号:US17798152

    申请日:2021-04-09

    Applicant: Google LLC

    CPC classification number: G06N20/00

    Abstract: A first multi-party computation (MPC) system of an MPC cluster can receive, from an application on a client device, an inference request comprising a first share of a given user profile for a user of the application and a performance threshold. A set of nearest neighbors to the user profile can be identified by performing a secure MPC process using a trained machine learning model in collaboration with one or more second MPC systems. One or more nearest neighbors having a performance measure that satisfies the performance threshold can be selected from the set of nearest neighbors. The first MPC system can transmit data derived from the one or more nearest neighbors to the application.

    Preventing fraud in aggregated network measurements

    公开(公告)号:US11736459B2

    公开(公告)日:2023-08-22

    申请号:US17419060

    申请日:2020-12-11

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including a method for preventing fraud. In some aspects, a method includes: receiving, from multiple client devices, a measurement data element that includes a respective group member key and a group identifier for a given conversion as a result of displaying a digital component. Each client device uses a threshold encryption scheme to generate, based at least on network data that includes one or more of impression data or conversion data for the conversion, a group key that defines a secret for encrypting the network data and generate, based on data related to the application, the respective group member key that includes a respective share of the secret. In response to determining that at least the threshold number of measurement data elements having the same group identifier have been received, the network data is decrypted using the group member keys in the received measurement data elements.

    Automatically detecting unauthorized re-identification

    公开(公告)号:US11720710B2

    公开(公告)日:2023-08-08

    申请号:US17375665

    申请日:2021-07-14

    Applicant: Google LLC

    CPC classification number: G06F21/6254 G06F21/6263 G06N5/04 G06N20/00

    Abstract: The present disclosure provides systems and methods for automatically detecting third-party re-identification of anonymized computing devices. The method includes retrieving a log of content items provided to anonymized computing devices identifying a first content item provided to a plurality of anonymized computing devices within a first predetermined time period; for each anonymized computing device of the plurality of anonymized computing devices, generating a set of identifications of second content items retrieved by the anonymized computing device prior to receiving the first content item within a second predetermined time period; determining that signals or combinations of signals with a highest predictive ability between a first set of identifications and a second set of identifications exceeds a threshold; identifying a provider of the first content item; and if the signals or combinations of signals with the highest predictive ability exceeds the threshold, preventing, transmission of a request of an anonymized computing device for a content item to the identified provider.

    Content selection using distribution parameter data

    公开(公告)号:US11704701B1

    公开(公告)日:2023-07-18

    申请号:US17466131

    申请日:2021-09-03

    Applicant: Google LLC

    Inventor: Gang Wang

    CPC classification number: G06Q30/0275 G06F16/24578 G06F16/9535 G06Q30/0251

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting content items for presentation along with publisher resources. In one aspect, a method includes receiving a request for a content item for presentation at a user device with a publisher resource; receiving, from a content item provider a first selection value for each of a plurality of content items provided by the content item provider; determining, for each of the content items and using accessed distribution parameters, a second selection value distinct from the first selection value; and determining, for each of the content items and independent of a bid corresponding to the content item, a combined selection value based on the first selection value for the content item and the second selection value for the content item.

    PREVENTING DATA MANIPULATION AND PROTECTING USER PRIVACY IN TELECOMMUNICATION NETWORK MEASUREMENTS

    公开(公告)号:US20230068395A1

    公开(公告)日:2023-03-02

    申请号:US17423579

    申请日:2020-05-20

    Applicant: Google LLC

    Abstract: This disclosure relates to generating telecommunication network measurements. In one aspect, a method includes presenting, by a client device, a digital component that, when interacted with, initiates a call by the client device to a phone number specified by the digital component. A trusted program stores, in a presentation event data structure, a presentation event data element specifying the phone number and resource locator for a reporting system to which reports for the digital component are sent. The trusted program detects a phone call by the client device to a given phone number. The given phone number is compared to one or more presentation event data elements stored in the presentation event data structure. A determination is made that the given phone number matches the phone number specified by the digital component. In response, an event report is transmitted to the reporting system.

    IMPROVING DATA INTEGRITY WITH TRUSTED CODE ATTESTATION TOKENS

    公开(公告)号:US20230050546A1

    公开(公告)日:2023-02-16

    申请号:US17053287

    申请日:2020-04-23

    Applicant: Google LLC

    Abstract: Methods, systems, and computer readable medium for verifying interactions with digital components. The method includes receiving input indicating interaction associated with a digital component that is provided by a content provider and presented by a user interface of the user device, determining, by a trusted program of the user device, that the interaction is valid, generating, by the trusted program and based on the determination that the interaction is valid based on a validity evaluation, a digitally signed token that attests the validity of the interaction with the digital component, and providing, by the trusted program and to a third party, the digitally signed token as an indication of the validity of the interaction.

    CRYPTOGRAPHICALLY SECURE REQUEST VERIFICATION

    公开(公告)号:US20230050222A1

    公开(公告)日:2023-02-16

    申请号:US17791966

    申请日:2020-10-27

    Applicant: GOOGLE LLC

    Abstract: This disclosure relates to data security and cryptography. In one aspect, a method includes updating a user interface of a client device to present user interface controls that enable a user to specify data privacy settings that define how entities collect, store, and use data of the user. The data security system receives a request to modify a data privacy setting for one or more entities from the client device based on user interaction with one or more of the user interface controls. The request includes an ephemeral user identifier for the user and an attestation token. The data security system validates the request using at least the ephemeral user identifier and the attestation token. The data security system transmits data instructing the entity to modify usage of the user data based on the modified given data privacy setting to each of the one or more entities.

    PRIVACY PRESERVING CENTROID MODELS USING SECURE MULTI-PARTY COMPUTATION

    公开(公告)号:US20220394102A1

    公开(公告)日:2022-12-08

    申请号:US17775994

    申请日:2021-09-16

    Applicant: GOOGLE LLC

    Abstract: This disclosure relates to a privacy preserving machine learning platform. In one aspect, a method includes receiving, from a client device and by a computing system of multiple multi-party computation (MPC) systems, a first request for user group identifiers that identify user groups to which to add a user. The first request includes a model identifier for a centroid model, first user profile data for a user profile of the user, and a threshold distance. For each user group in a set of user groups corresponding to the model identifier, a centroid for the user group that is determined using a centroid model corresponding to the model identifier is identified. The computing system determines a user group result based at least on the first user profile data, the centroids, and the threshold distance. The user group result is indicative of user group(s) to which to add the user.

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