In one embodiment, this invention analyzes demographic data that is associated with a specific street address when presented as an address change on an existing account or an address included on a new account application when that address is different from the reference address (e.g., a credit bureau type header data). The old or reference address and the new address, the new account application address or fulfillment address demographic attributes are gathered, analyzed, compared for divergence and scaled to reflect the relative fraud risk.

A system and method for resolving an unsatisfactory quality of experience (QoE) for an application executed on a wireless device that accesses a CSP network is described. A QoE network appliance generates an integrated event stream that includes a RAN data set, a CN data set, a NWDAF data set, a QoE latency measurement, a QoE bandwidth measurement, and a QoE packet loss rate measurement. A measured QoE score is generated with the RAN data set, the CN data set, and the NWDAF data set. The measured QoE score is associated with a QoE latency measurement, a QoE bandwidth measurement, and a QoE packet loss rate measurement. A robotics process automation (RPA) module receives the integrated event stream when the measured QoE score fails to satisfy the QoE requirement. The RPA module performs one or more automated actions to improve the measured QoE based on information from the integrated event stream.

A method including: receiving a user report dataset indicating fraudulent activity corresponding to a phone number; responsive to receiving the user report dataset, identifying a record in a database corresponding to the phone number; and tagging the record to identify the phone number as being associated with fraudulent activity.

An example method performed by a processing system obtaining a first port-in number for a first mobile device from a first mobile communications service provider, wherein the first port-in number is known to be involved in fraudulent activity, constructing a social graph of communications between the first port-in number and a plurality of other numbers associated with a plurality of other communications devices, identifying, by the processing system, a maximal subgraph of the social graph, wherein the maximal subgraph connects the first port-in number and a subset of the plurality of other numbers that includes those of the plurality of other numbers for which a usage metric is below a predefined threshold for a defined period of time prior to the first port-in number being ported into the first mobile communications service provider, and identifying, by the processing system, a potential fraud ring, based on the maximal subgraph.

Method for detecting fraudulent or abusive use of telephone services comprising the following steps: collecting data on telephone communication exchanges carried out over a given study period from/to telephone numbers and involving roaming and/or interconnection; creating individual files for compiling exchange data for each studied number; revaluing communications based on pre-established revaluation rules to obtain a wholesale cost amount for each studied number; a step E4 of identifying suspicious numbers for which the amount of wholesale costs exceeds a predetermined threshold value over the study period; a step E7 of detecting fraudulent use by analysing exchange data compiled in the files associated with the identified numbers and/or the multiparametric indicators obtained from said data.

Methods for detecting fraudulent or abusive use of telephone services.

A browser executing on a client device can detect external calls to remote servers generated by an online document. The browser can detect, in external content received in response to the external calls and for presentation in the online document, metadata describing domains that contributed to the delivery of the external content to the client device. The browser can aggregate, for each of the domains, a contribution of the domain to enable the presentation of the external content with the online document over a specified time period. The browser can present a visual representation of the contribution of each of at least some of the domains. The browser can receive, in response to interaction with the visual representation, a selection of one or more domains among the at least some domains. The browser can prevent the one or more domains from receiving subsequent external calls from the browser.

Secure architectures and methods for improving the security of mobile devices are disclosed. Also disclosed are apparatuses and methods to detect and mitigate fraud in device-assisted services implementations.

Unsolicited electronic communications such as robocalls and person-initiated solicitation calls are reduced by imposing tolls for completion of the connections to the called parties, and refunding the tolls to the entities indicated by the electronic communications as the calling parties. In this way, a dishonest originator of a spoofed call bears the cost of the toll, and the toll is not refunded to the dishonest originator. On the other hand, the toll collected from an honest originator of a non-spoofed call is refunded to the honest originator, making the toll transparent to the honest originator and avoiding annoyance of the honest caller caused by the toll. Unsolicited calls may be subjected to filtering, particularly filtering based on the indications of the origins of the calls.

One or more computing devices, systems, and/or methods for identifying anomalous behavior of users are provided. In an example, users of a telecommunication service provider may be segmented into a plurality of user segments based upon telecommunication service metrics associated with the users. A machine learning model may be trained using telecommunication service information associated with users of the first user segment to generate a trained machine learning model. Using the trained machine learning model, a forecast of telecommunication service usage associated with a first user segment of the plurality of user segments. A telecommunication service usage metric, associated with a user belonging to the first user segment, may be compared with a range indicated by the forecast. The user may be flagged as having anomalous behavior based upon a determination that one or more telecommunication usage metrics, associated with the user, are outside one or more ranges indicated by the forecast.

The present specification provides a blockchain-based data verification system and method, a computing device, and a storage medium. The blockchain-based data verification system includes: a first verification system, a second verification system, and a first blockchain node and a second blockchain node on a blockchain network; the first verification system is configured to: collect first service data based on a predetermined condition and generate a first verification file including the first service data, and send a verification request to the second verification system; the second verification system is configured to: receive the verification request, verify the first service data with second service data in a local database of the second verification system, generate and send a verification result notification to the first verification system, and send successfully verified second service data in the local database to the first blockchain node on the blockchain network; wherein the first verification system is further configured to: receive the verification result notification, and send successfully verified first service data to the second blockchain node on the blockchain network.