Abstract: A user consent service that collects information on the type of data users have consented to sharing with different service providers (location information, account status, etc.), so that mobile network operators determine whether to approve or deny user information requests. The service receives information from service providers (e.g., websites, cloud services, mobile applications, and other network-accessible resources) which indicates that users have consented to the sharing of certain types of user data with those service providers. In response, the user consent service maintains records cataloging the consent received for the users, including what type of data that the users have consented to sharing with the different service providers (i.e., what pieces of data may or may not be shared with the different server providers). The service generates consent data for mobile network operators, from the records, so the mobile network operators can evaluate requests for user data.

Abstract: A user consent service that collects information on the type of data users have consented to sharing with different service providers (location information, account status, etc.), so that mobile network operators determine whether to approve or deny user information requests. The service receives information from service providers (e.g., websites, cloud services, mobile applications, and other network-accessible resources) which indicates that users have consented to the sharing of certain types of user data with those service providers. In response, the user consent service maintains records cataloging the consent received for the users, including what type of data that the users have consented to sharing with the different service providers (i.e., what pieces of data may or may not be shared with the different server providers). The service generates consent data for mobile network operators, from the records, so the mobile network operators can evaluate requests for user data.

Abstract: A system and methods for assessing risk of fraud associated with a unique identifier associated with a telecommunication device of a user. The disclosed system utilizes one or more datasets of traffic representing network sessions over a telecommunications network. The system uses machine learning techniques to analyze network session data and/or static or dynamic attributes characterizing the network session data, and generates a risk scoring model that assesses the likelihood that the user is associated with fraudulent activities. The system receives a unique identifier and queries the one or more datasets for data characterizing traffic over the telecommunications network associated with the unique identifier. The system analyzes the traffic data associated with the unique identifier based on the risk scoring model and generates a score, grade, reason code, or other characterization indicating the likelihood of fraud associated with the unique identifier.

Abstract: A user consent service that collects information on the type of data users have consented to sharing with different service providers (location information, account status, etc.), so that mobile network operators determine whether to approve or deny user information requests. The service receives information from service providers (e.g., websites, cloud services, mobile applications, and other network-accessible resources) which indicates that users have consented to the sharing of certain types of user data with those service providers. In response, the user consent service maintains records cataloging the consent received for the users, including what type of data that the users have consented to sharing with the different service providers (i.e., what pieces of data may or may not be shared with the different server providers). The service generates consent data for mobile network operators, from the records, so the mobile network operators can evaluate requests for user data.