Example embodiments of the present disclosure provide an order data interaction method and a server. The interaction method includes: receiving an order request sent by a first communication terminal, and acquiring a first communication number according to the order request; allocating a second communication number to the first communication number, and setting a correlation between the first communication number and the second communication number; sending correlation information to a basic communication server, in which the correlation information carries the first communication number and the second communication number; binding the second communication number with the order request; and sending the order request having a binding relation with the second communication number to a second communication terminal. The data interaction method effectively avoids leakage of users' telephone numbers.

One example method may include identifying a call notification of a call intended for a mobile device, retrieving call data having a code object identifier with the call notification, forwarding the call data with a code object to the mobile device based on the code object identifier prior to forwarding the call, and forwarding the call to the mobile device.

Novel tools and techniques are provided for implementing automated robocall detection. In various embodiments, a computing system may compare first abstracted raw data, obtained from a portion of call data from a first call from a first originating party, with each of a plurality of abstracted raw data, obtained from portions of call data from a plurality of calls from a corresponding plurality of originating parties. In some instances, the plurality of abstracted raw data and the first abstracted raw data may each include at least one of word count data, phoneme count data, inter-word timing data, voice pitch estimation data, and/or background noise data. The computing system may determine whether the first abstracted raw data is indicative of the first call being a suspected unsolicited or unwanted communication, based at least in part on the comparison. If so, the computing system may perform one or more tasks.

One example method may include identifying a call notification of a call intended for a mobile device, retrieving call data having a code object identifier with the call notification, forwarding the call data with a code object to the mobile device based on the code object identifier prior to forwarding the call, and forwarding the call to the mobile device.

Systems, methods, and computer-readable media are provided for telephone number provisioning. A user interface configured to provide access to telephony information may be facilitated. The telephony information may be retained in a telephony information repository. Information about a first location may be processed. A region of interest may be determined. A set of telephony information may be processed based on the region of interest. Telephone number inventory corresponding to the region of interest may be determined based in part on the set of telephony information. Telephone number inventory may be categorized according to availability to determine a first set of telephone numbers. Local calling characteristics may be determined. Indication to the user interface of availability of telephone numbers within the region of interest based on the first set of telephone numbers and the local calling characteristics may be caused. The user interface may present graphical indicia that distinguishes the local calling characteristics.

Techniques for verifying identity and/or location of a customer. One embodiment involves receiving a customer-provided address from a customer in a communication via a computer network or telephone network. The customer is a person or entity paying to receive calls from a resident of a controlled access residential institution. The embodiment further involves accessing a computer system to identify location information associated with the customer, the location information derived from additional information within or about the communication and determining a reliability estimate of the customer-provided address by comparing the customer-provided address with the location information associated with the customer that was identified based on the additional information. The embodiment may involve notifying a telecommunications provider, the controlled access residential institution, or law enforcement based on the reliability estimate of the customer-provided address.

Novel tools and techniques are provided for implementing automated robocall detection. In various embodiments, a computing system may compare first abstracted raw data, obtained from a portion of call data from a first call from a first originating party, with each of a plurality of abstracted raw data, obtained from portions of call data from a plurality of calls from a corresponding plurality of originating parties. In some instances, the plurality of abstracted raw data and the first abstracted raw data may each include at least one of word count data, phoneme count data, inter-word timing data, voice pitch estimation data, and/or background noise data. The computing system may determine whether the first abstracted raw data is indicative of the first call being a suspected unsolicited or unwanted communication, based at least in part on the comparison. If so, the computing system may perform one or more tasks.

A system for identification of a fraudulent voice call in real-time is described. The system includes a first device configured to receive a voice call originating from a second device and generate a call forward request. A server is configured to, in response to the call forward request, divide the voice call into a plurality of audio signals and analyze one or more audio signals to identify whether an audio originating from the second device is a cloned voice or a human voice. The server is configured to analyze the audio signal along with one or more preceding audio signals to determine a risk score associated with an identification of a fraudulent activity during the voice call and identify the voice call as the fraudulent voice call. The server is configured to trigger an alert in the first device to indicate that the voice call is a fraudulent voice call.

Novel tools and techniques are provided for implementing call center-based automated interface with voice switches for voice service diagnostics and provisioning. In various embodiments, in response to receiving a request by a call center user to access a voice service customer account, a computing system may access information regarding the voice service customer account that is stored in a database, may identify a switch that is configured to control voice service to a customer premises associated with the customer, based at least in part on the accessed information, and may autonomously access, from other databases, information associated with the voice service customer account. The computing system may integrate the accessed information, may generate and present a user interface (UI) displaying the accessed information, and may generate and present one or more options within the UI for the call center user to select to change features of the voice service.

There is disclosed in one example a mobile telephone, including: a hardware platform including a processor and a memory; a telecommunication transceiver; and instructions encoded within the memory to instruct the processor to: identify a call made via the telecommunication transceiver; analyze the call and assign the call a predicted local reputation according to the analysis, including a legitimacy confidence score; if the legitimacy confidence score is less than a first threshold, terminate the call; if the legitimacy confidence score is greater than a second threshold, cease analysis of the call; and if the legitimacy confidence score is between the first and second thresholds, continue analysis of the call.