Abstract: This disclosure relates to using probabilistic data structures to enable systems to detect fraud while preserving user privacy. In one aspect, a method includes obtaining a set of frequency filters. Each frequency filter defines a maximum event count for a specified event type over a specified time duration and corresponds to a respective content provider. A subset of the frequency filters are identified as triggered frequency filters for which an actual event count for the specified event type corresponding to the frequency filter exceeds the maximum event count defined by the frequency filter during a time period corresponding to a specified time duration for the frequency filter. A probabilistic data structure that represents at least a portion of the frequency filters in the subset of frequency filters is generated. A request for content is sent to multiple content providers. The request for content includes the probabilistic data structure.

Abstract: This disclosure relates to using probabilistic data structures to enable systems to detect fraud while preserving user privacy. In one aspect, a method includes obtaining a set of frequency filters. Each frequency filter defines a maximum event count for a specified event type over a specified time duration and corresponds to a respective content provider. A subset of the frequency filters are identified as triggered frequency filters for which an actual event count for the specified event type corresponding to the frequency filter exceeds the maximum event count defined by the frequency filter during a time period corresponding to a specified time duration for the frequency filter. A probabilistic data structure that represents at least a portion of the frequency filters in the subset of frequency filters is generated. A request for content is sent to multiple content providers. The request for content includes the probabilistic data structure.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting errors in a client device and its associated applications while preserving the privacy of the user of the device. Methods can include obtaining and blinding contextual application data for an application on a device. Data regarding the application's digital certificate and device trustworthiness data are obtained and provided to a trust assessment server along with the blinded data. This server can provide indications that the device is trustworthy and the application is authentic, and can digitally sign the blinded data. The digital signature can be validated and the unblinded contextual application data can be obtained. If the unblinded data matches the contextual application data, the application can provide the digital signature, the indications, and the unblinded contextual application data to an error detection server, which in turn can indicate the application does not have errors.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting errors in a client device and its associated applications while preserving the privacy of the user of the device. Methods can include obtaining and blinding contextual application data for an application on a device. Data regarding the application's digital certificate and device trustworthiness data are obtained and provided to a trust assessment server along with the blinded data. This server can provide indications that the device is trustworthy and the application is authentic, and can digitally sign the blinded data. The digital signature can be validated and the unblinded contextual application data can be obtained. If the unblinded data matches the contextual application data, the application can provide the digital signature, the indications, and the unblinded contextual application data to an error detection server, which in turn can indicate the application does not have errors.

Abstract: This disclosure relates to using trust tokens to verify the integrity of devices and applications from which data is received. In one aspects, a method includes receiving, from a client device, a request for one or more trust tokens. The request includes at least one of one or more device-level fraud detection signals obtained from the client device or data representing code of an application that initiated the request. The request also includes a respective nonce for each of the one or more trust tokens. A determination is made, based on at least one of the one or more device-level fraud signals or the data representing the code of the application, to issue the one or more trust tokens to the client device. Each trust token is generated using the nonce for the trust token. The one or more trust tokens are provided to the client device.

Abstract: 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.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for verifying content provided for display within a webview and interactions with such content. Methods can include providing, within a webview executing in a portion of an application launched on a client device, a first content page including a digital component and detecting, by a script executing within the webview, a set of interaction signals. After detection of the set of interaction signals, the signals can be transferred from the webview, via a communication bridge, to a software library that is resident within the native layer. The software library transmits the set of interaction signals to a first content provider, which can determine whether the interaction signals indicate interactions by an actual human user as opposed to automated interactions. The software library then launches a second content page that is linked to by the digital component.

Abstract: This disclosure relates to using trust tokens to verify the integrity of devices and applications from which data is received. In one aspects, a method includes receiving, from a client device, a request for one or more trust tokens. The request includes at least one of one or more device-level fraud detection signals obtained from the client device or data representing code of an application that initiated the request. The request also includes a respective nonce for each of the one or more trust tokens. A determination is made, based on at least one of the one or more device-level fraud signals or the data representing the code of the application, to issue the one or more trust tokens to the client device. Each trust token is generated using the nonce for the trust token. The one or more trust tokens are provided to the client device.

Abstract: This disclosure relates to using probabilistic data structures to enable systems to detect fraud while preserving user privacy. In one aspect, a method includes obtaining a set of frequency filters. Each frequency filter defines a maximum event count for a specified event type over a specified time duration and corresponds to a respective content provider. A subset of the frequency filters are identified as triggered frequency filters for which an actual event count for the specified event type corresponding to the frequency filter exceeds the maximum event count defined by the frequency filter during a time period corresponding to a specified time duration for the frequency filter. A probabilistic data structure that represents at least a portion of the frequency filters in the subset of frequency filters is generated. A request for content is sent to multiple content providers. The request for content includes the probabilistic data structure.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting errors in a client device and its associated applications while preserving the privacy of the user of the device. Methods can include obtaining and blinding contextual application data for an application on a device. Data regarding the application's digital certificate and device trustworthiness data are obtained and provided to a trust assessment server along with the blinded data. This server can provide indications that the device is trustworthy and the application is authentic, and can digitally sign the blinded data. The digital signature can be validated and the unblinded contextual application data can be obtained. If the unblinded data matches the contextual application data, the application can provide the digital signature, the indications, and the unblinded contextual application data to an error detection server, which in turn can indicate the application does not have errors.