A system and method may identify a fraud ring based on call or interaction data by analyzing by a computer processor interaction data including audio recordings to identify clusters of interactions which are suspected of involving fraud each cluster including the same speaker; analyzing by the computer processor the clusters, in combination with metadata associated with the interaction data, to identify fraud rings, each fraud ring describing a plurality of different speakers, each fraud ring defined by a set of speakers and a set of metadata corresponding to interactions including that speaker; and for each fraud ring, creating a relevance value defining the relative relevance of the fraud ring.

Disclose herein are embodiments related to a system made up of a lighting fixture and a radio frequency detection device. The lighting fixture having a secure housing and at least one power connection, and the radio frequency detection device being designed to operatively connect to the at least one power connection device within the lighting fixture.

A system for controlling, monitoring, and recording of wireless telecommunications services associated with penal institutions is provided comprising a portable electronic device and application executing on the device that present a listing of available call destinations based on receiving a first instruction from a first authorized party possessing the device. The application receives a second instruction comprising a choice of a first call destination from the listing. The application transmits a third instruction requesting connection with the destination and joins a second authorized party associated with the first call destination in a first voice session. The application joins the first authorized party to the first session. The application further joins the first party to a second voice session initiated by the second party based on determining that the second party initiated the second session from the first destination. The device originates and receives transmissions solely upon approval of the application.

A method and system for intercepting mobile apparatus of cellular radio system are disclosed. The method can include implementing, with an interrogation apparatus, a silent call with a mobile apparatus in a radio cell; implementing, with a mobile platform, at least three transmit radio beams each with a distinct transmission direction in relation to the mobile platform; receiving a measurement report from the mobile apparatus including received downlink power levels of the radio cell and at least one of the three transmit radio beams; receiving a geographical location of the mobile platform; obtaining a geographical orientation of the mobile platform; and calculating a geographical location of the mobile apparatus based on the received downlink power levels, the geographical location of the mobile platform, the distinct transmission directions, and the geographical orientation of the mobile platform.

Disclosed is a secure telephone call management system for authenticating users of a telephone system in an institutional facility. Authentication of the users is accomplished by using a personal identification number, preferably in conjunction with speaker independent voice recognition and speaker dependent voice identification. When a user first enters the system, the user speaks his or her name which is used as a sample voice print. During each subsequent use of the system, the user is required to speak his or her name. Voice identification software is used to verify that the provided speech matches the sample voice print. The secure system includes accounting software to limit access based on funds in a user's account or other related limitations. Management software implements widespread or local changes to the system and can modify or set any number of user account parameters.

An anti-communications fraud apparatus 1 includes: an analysis unit 13 that analyzes a voiceprint of a communication voice of a calling party; a determination unit 14 that acquires, from a database 17 in which the voiceprint and a degree of fraud risk are stored in association with each other, the degree of fraud risk corresponding to the voiceprint of the calling party, and determines whether the degree of fraud risk exceeds a predetermined threshold; and a notification unit 15 that notifies that the calling party is dangerous when the degree of fraud risk exceeds the threshold.

According to an embodiment of the disclosure, a toll-free telecommunications validation system determines a confidence value that an incoming phone call to an enterprises' toll-free number is originating from the station it purports to be, i.e., is not a spoofed call by incorporating one or more layers of signals and data in determining said confidence value, the data and signals including, but not limited to, toll-free call routing logs, service control point (SCP) signals and data, service data point (SDP) signals and data, dialed number information service (DNIS) signals and data, automatic number identification (ANI) signals and data, session initiation protocol (SIP) signals and data, carrier identification code (CIC) signals and data, location routing number (LRN) signals and data, jurisdiction information parameter (JIP) signals and data, charge number (CN) signals and data, billing number (BN) signals and data, and originating carrier information (such as information derived from the ANI, including, but not limited to, alternative service provider ID (ALTSPID), service provider ID (SPID), or operating company number (OCN)). In certain configurations said enterprise provides an ANI and DNIS associated with said incoming toll-free call, which is used to query a commercial toll-free telecommunications routing platform for any corresponding log entries. The existence of any such log entries, along with the originating carrier information in the event log entries do exist, is used to determine a confidence value that said incoming toll-free call is originating from the station it purports to be. As a result, said entities or enterprises operating a toll-free number may be provided a confidence value regarding an incoming telephone call, and using that confidence value, further determine whether or not to accept the authenticity of the incoming telephone call and/or based on said confidence value, service the incoming call differently.

Techniques for tracking and display of compliance with instructions provided by emergency call takers are provided. An artificial intelligence (AI) bot monitors a conversation between an emergency caller and an emergency call taker. The AI bot identifies at least one instruction issued by the emergency call taker to the emergency caller. The AI bot determines when execution of the at least one instruction has been confirmed.

Disclosed is a secure telephone call management system for authenticating users of a telephone system in an institutional facility. Authentication of the users is accomplished by using a personal identification number, preferably in conjunction with speaker independent voice recognition and speaker dependent voice identification. When a user first enters the system, the user speaks his or her name which is used as a sample voice print. During each subsequent use of the system, the user is required to speak his or her name. Voice identification software is used to verify that the provided speech matches the sample voice print. The secure system includes accounting software to limit access based on funds in a user's account or other related limitations. Management software implements widespread or local changes to the system and can modify or set any number of user account parameters.

An example method is described. The method includes receiving, by a computing system, data indicative of a call into an interactive voice response (IVR) system from a user device and determining, by the computing system and based on the data, a set of actions performed by the user device within the IVR system and a corresponding set of results performed by the IVR system during the call. Additionally, the method includes converting, by the computing system, the set of actions and the corresponding set of results into a sequence of code pairs using a dictionary established based on training data, determining, by the computing system, an activity pattern during the call based on the sequence of code pairs; and calculating, by the computing system, a probability that the call is fraudulent based on the activity pattern during the call.