Using secure multi-party computation and probabilistic data structures to protect access to information

    公开(公告)号:US12231547B2

    公开(公告)日:2025-02-18

    申请号:US17924561

    申请日:2021-12-13

    Applicant: Google LLC

    Abstract: 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.

    Cryptographically secure control using secure multi-party computation

    公开(公告)号:US12200100B2

    公开(公告)日:2025-01-14

    申请号:US17927049

    申请日:2022-08-22

    Applicant: GOOGLE LLC

    Abstract: This document describes systems and techniques for using secure MPC to select digital components in ways that preserve user privacy and protects the security of data of each party that is involved in the selection process. In one aspect, a method includes obtaining, by a first computer of a secure multi-party computation (MPC) system, at least a first share of a set of contextual properties of an environment in which a selected digital component will be displayed at a client device. For each digital component in a set of digital components, at least a first share of an eligibility expression that defines a relationship between a set of eligibility criteria for the digital component is obtained. A determination is made, based on the at least first share of the set of contextual properties and the at least first share of the eligibility expression, a first share of an eligibility parameter.

    COMBATING FALSE INFORMATION WITH CROWDSOURCING

    公开(公告)号:US20250014071A1

    公开(公告)日:2025-01-09

    申请号:US18895735

    申请日:2024-09-25

    Applicant: Google LLC

    Inventor: Gang Wang Yian Gao

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for combating false advertising using crowdsourcing. In one aspect, a method includes receiving a false digital component alert indicating that a digital component presented at a client device includes false information, validating the false digital component alert based on a public key to verify digital signature included in the false digital component alert matching the public key of stored attestation tokens specifying presentation and interaction data for the digital component. In response, adding the false digital component alert to an aggregated report. Based on a false alert ratio, determining that a magnitude of validated false digital component alerts in the aggregated report meets a threshold, and triggering a false digital component mitigation response including providing a false information warning with the false digital component to one or more client devices or digital component provider.

    PRIVACY PRESERVING DATA COLLECTION AND ANALYSIS

    公开(公告)号:US20240427931A1

    公开(公告)日:2024-12-26

    申请号:US18829879

    申请日:2024-09-10

    Applicant: Google LLC

    Abstract: A method includes receiving, by a data processing apparatus and from a content distribution system, a message comprising a probabilistic data structure representing a set of content items that should not be provided to a user device, content item data for content items available to be provided, and a request to determine whether any content item data is invalid, determining that the content item data for a given content item is invalid because the given content item may be in the set of content items represented by the probabilistic data structure, including removing the content item data for the given content item that was determined to be invalid; and preventing distribution of content items including the given content item.

    Privacy preserving centroid models using secure multi-party computation

    公开(公告)号:US12149594B2

    公开(公告)日:2024-11-19

    申请号:US18497576

    申请日:2023-10-30

    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.

    Privacy-preserving cross-domain experimental group partitioning and monitoring

    公开(公告)号:US12130893B2

    公开(公告)日:2024-10-29

    申请号:US17924897

    申请日:2022-04-05

    Applicant: Google LLC

    CPC classification number: G06F21/10 G06F21/6245

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for privacy-preserving cross-domain experiment monitoring are described. In one aspect, a method includes receiving, by a first server of a MPC system, a request for digital content including a first secret share of an application instance identifier that identifies the application instance associated with the device. The first server conducts, in collaboration with a second server of the secure MPC system, a privacy-preserving selection process to select a winning digital component from a set of digital components. Each digital component has a corresponding unique experiment identifier and unique control identifier. A first secret share representing the winning digital component is generated. A response is generated and includes the first secret share of the selection result and data representing whether the application is in the experiment group or a control group for each digital component.

    EFFICIENT GARBLED CIRCUIT PROTOCOL FOR SECURE MULTI-PARTY COMPUTATION

    公开(公告)号:US20240313953A1

    公开(公告)日:2024-09-19

    申请号:US18410434

    申请日:2024-01-11

    Applicant: Google LLC

    CPC classification number: H04L9/085

    Abstract: This document describes systems and techniques for using cryptography, secret sharing, secure MPC, garbled circuits, and oblivious transfer to select digital components in ways that preserve user privacy and protects the security of data of each party that is involved in the selection process. A method includes obtaining, by a first computer of a secure multi-party computation (MPC) system, at least a first share of user data related to a user of a client device. For each digital component in a set, a first secret share of a condition bit for the condition is obtained for each of one or more conditions that condition eligibility of the digital component for distribution. A garbled circuit is executed to select a given digital component for which each of the one or more conditions of the digital component is satisfied using the first secret share and the second secret share for each condition.

    Cryptographically secure data protection

    公开(公告)号:US12039078B2

    公开(公告)日:2024-07-16

    申请号:US17617358

    申请日:2020-10-27

    Applicant: Google LLC

    CPC classification number: G06F21/6245 G06F21/604 H04L63/0428 H04L67/53

    Abstract: This disclosure relates to data security and cryptography. In one aspect, a method includes receiving a request for a subscription token for a given user by a data security system from a publisher computing system of a publisher. The request includes user identification information provided to the publisher by the given user when subscribing to electronic content of the publisher. The data security system generates the subscription token which includes a set of data that includes a first encrypted user identifier generated by encrypting a first user identifier for the given user using an encryption key of the data security system, and, for each of one or more content platforms, an attachment element that includes a second encrypted user identifier generated by encrypting a second user identifier for the given user using an encryption key of the content platform and transmitting the subscription token to the publisher computing system.

    PREVENTING DATA MANIPULATION USING MULTIPLE AGGREGATION SERVERS

    公开(公告)号:US20240214219A1

    公开(公告)日:2024-06-27

    申请号:US18417666

    申请日:2024-01-19

    Applicant: Google LLC

    CPC classification number: H04L9/3257 H04L9/0822 H04L9/0825 H04L9/14

    Abstract: Methods, systems, and apparatus, including a method for determining network measurements. In some aspects, a method includes receiving, by a first aggregation server and from each of multiple client devices, encrypted impression data. A second aggregation server receives, from each of at least a portion of the multiple client devices, encrypted conversion data. The first aggregation server and the second aggregation server perform a multi-party computation process to decrypt the encrypted impression data and the encrypted conversion data. Each portion of decrypted impression data and each portion of decrypted conversion data is sent to a respective reporting system.

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