The disclosed technology includes at least one method that enables a user of a wireless mobile device to remotely administer test cases that check the performance of telecommunications network nodes. The method includes authenticating a user for a limited time period in which the user can remotely administer the test cases. While being temporarily authenticated, the user can configure the test cases by associating services or operations with particular nodes. The executed test cases cause the nodes to generate data that indicate performance of the nodes in response to the services or operations. The results can be displayed at the mobile device used to remotely administer the test cases.

Disclosed herein are systems and methods for providing mobile call authentication. For instance, a token indicative of a call request can be received from a calling party. The token can include a called party number and a time of the request. A subscriber database can be accessed to determine identifying information associated with the calling party based at least in part on the token. The token can be authenticated based at least in part on the identifying information and using one or more predefined authentication protocols. The token can be stored in a call session registry storing data indicative of a plurality of active telephone call events. A verification request for the call request can be received from the called party. The call request can be verified based at least in part on the token. The called party can be notified that the call request has been verified.

Systems for and methods of training a spoofing detection model include receiving a plurality of customer call interactions; classifying each of the plurality of customer call interactions as a spoofed call or a non-spoofed call using a spoofing detection model; generating a voiceprint for each of the plurality of customer call interactions; comparing the generated voiceprints; grouping the generated voiceprints into one or more clusters based on the comparing, wherein each cluster represents a single speaker; locating a cluster containing a spoofed call and a non-spoofed call, thereby indicating that the non-spoofed call was misclassified by the spoofing detection model; and updating the spoofing detection model with the non-spoofed call.

Disclosed is an incoming call processing method, applied to a mobile terminal and including: after receiving an incoming call carrying an INVITE signaling, determining, according to the INVITE signaling, a type of a calling number corresponding to the incoming call; determining whether the incoming call is a malicious call based on the type of the calling number; and intercepting the incoming call when it is determined that the incoming call is a malicious call. Also disclosed are a mobile terminal and a computer storage medium.

The subject matter described herein provides systems and techniques for adding an identity (ID) header to IP packets associated with a VoIP call. This ID header may be used to authenticate the source provider/originator of a VoIP call, may be used to traceback to the source provider/originator of the VoIP call, and may be used to create a relationship between the source provider/originator and the destination provider/destination of the VoIP call. Such steps may be performed by a public proxy/platform. The ID header may include a certificate and/or a public encryption key, from a public certificate authority (CA) infrastructure, which assists in authenticating the source provider/originator of the VoIP call. The public proxy/platform may directly route authenticated VoIP calls through a VoIP network towards its destination, bypassing a public switched telephone network (PSTN).

The VOIP call security is enhanced using the caller's geographical location information, which is transmitted to the home network device using an unmodifiable header. The home network device checks the veracity of the caller's geographical location information to determine whether the caller is suspicious.

An example system for performing call center tasks with the assistance of a human operator comprises a plurality of remote electronic devices and a system server. Each of the plurality of remote electronic devices has a speaker, a microphone and a screen. The system server has a data store configured to store personal information and a dialing platform configured to connect the remote electronic devices with customer devices. The system server may transmit fragments of personal information to the remote electronic device and the remote electronic device may display the fragments of personal information on its screen as the human operator engages in the call with the customer over the remote electronic device.

Methods and apparatuses for managing spoofed calls to a mobile device are described, in which the mobile device receives a call transmitted over a cellular or mobile network. The call may include a set of information associated with the network, such as a geological location of a device that generated the call, a hardware device identifier corresponding to the device, an internet protocol (IP) address associated with the device, or a combination thereof. The mobile device may determine whether the call is spoofed or genuine based on the set of information. Subsequently, the mobile device may assist a user of the mobile device to manage the call, such as blocking the call from reaching the user, informing the user that the call is spoofed, facilitating the user to report the call as spoofed to an authority and/or a service provider of the network.

An illegal call detection apparatus comprises a data collecting unit, a preprocessing unit, and a learning unit. The data collecting unit collects, from at least one of a subscriber terminal or a call exchanger, a raw packet generated by the subscriber terminal using a VoIP service, and collects, from the billing server, CDR data related to the raw packet. The preprocessing unit generates learning data by using service usage information extracted from the CDR data and service detailed information extracted from the raw packet, and generates a training image by converting the training data into an image according to a predetermined imaging rule. The learning unit extracts at least one or more features from the training image, and learns whether the training image is related to an illegal call by using the features, through an illegal call detection model.

Disclosed herein are systems and methods for providing mobile call authentication. For instance, a token indicative of a call request can be received from a calling party. The token can include a called party number and a time of the request. A subscriber database can be accessed to determine identifying information associated with the calling party based at least in part on the token. The token can be authenticated based at least in part on the identifying information and using one or more predefined authentication protocols. The token can be stored in a call session registry storing data indicative of a plurality of active telephone call events. A verification request for the call request can be received from the called party. The call request can be verified based at least in part on the token. The called party can be notified that the call request has been verified.