Source: http://www.google.fr/patents/US6856982
Timestamp: 2013-06-19 03:57:09
Document Index: 388780

Matched Legal Cases: ['arty 108', 'arty 114', 'arty 114', 'arty 114', 'arty 108', 'arty 114', 'arty 108', 'arty 114', 'arty 108', 'arty 108', 'arty 114', 'arty 108', 'arty 114', 'arty 114', 'arty 114', 'arty 108', 'arty 114', 'arty 108', 'arty 114', 'arty 108', 'arty 114', 'arty 108', 'arty 108', 'arty 114', 'arty 114', 'arty 108', 'arty 114', 'arty 108', 'arty 108', 'arty 114', 'arty 114', 'arty 114', 'arty 114', 'arty 108', 'arty 114', 'arty 108', 'arty 114', 'arty 114', 'arty 108', 'arty 108', 'arty 108', 'arty 108', 'arty 108', 'arty 108', 'art 114', 'arty 108', 'arty 114', 'arty 108', 'arty 108']

Brevet US6856982 - System, intelligent network service engine and method for detecting a ... - Google�BrevetsRecherche Images Maps Play YouTube Actualit�s Gmail Drive Plus » Recherche avanc�e dans les brevets | Historique Web | Connexion Recherche avanc�e dans les brevets BrevetsA system, intelligent network service engine and method are described than can perform a real time fraud analysis on an originating side of a call stream to determine whether or not a call is a fraudulent call before the call is connected to a called party. In particular, the system includes a switch...http://www.google.fr/patents/US6856982?utm_source=gb-gplus-shareBrevet US6856982 - System, intelligent network service engine and method for detecting a fraudulent call using real time fraud management tools Num�ro de publicationUS6856982 B1Type de publicationOctroi Num�ro de demande09/795,246 Date de publication15 f�vr. 2005 Date de d�p�t26 f�vr. 2001 Date de priorit�26 f�vr. 2001 Num�ro de publication09795246, 795246, US 6856982 B1, US 6856982B1, US-B1-6856982, US6856982 B1, US6856982B1 InventeursBabu V. Mani, Gilman R. Stevens Cessionnaire d'origineAlcatelCitations de brevets (5), R�f�renc� par (4), Classifications (27) Liens externes: USPTO, Cession USPTO, EspacenetSystem, intelligent network service engine and method for detecting a fraudulent call using real time fraud management toolsUS 6856982 B1 R�sum� A system, intelligent network service engine and method are described than can perform a real time fraud analysis on an originating side of a call stream to determine whether or not a call is a fraudulent call before the call is connected to a called party. In particular, the system includes a switch capable of receiving a call originated by a calling party and an intelligent network service engine capable receiving information (e.g., call origination data) about the call from the switch. The intelligent network service engine (e.g., home location register, service control point, INSight platform) then uses real time fraud management tools to analyze the call origination data to determine whether or not the call has a fraudulent attribute before the call is connected to a called party. The system can be configured as a wired communications network, a wireless communications network and/or an Internet network.
1. A method for detecting a fraudulent call, said method comprising the steps of:
receiving, at an intelligent network service engine, a query about a call originated by a calling party; and preventing the connection of the call at least until a determination can be made as to whether the call has a fraudulent attribute, the determination made by using, at the intelligent network service engine, real time fraud management tools to analyze information within the query. 2. The method of claim 1, wherein if the call has a fraudulent attribute then the method further includes the step of blocking the fraudulent call.
3. The method of claim 1, wherein if the call has a fraudulent attribute then the method further Includes the step of forwarding the fraudulent call to a network announcement system.
4. The method of claim 1, wherein if the call has a fraudulent attribute then the method further includes the step of forwarding the fraudulent call to a fraud operator.
5. The method of claim 4, further comprising the step of obtaining validation information from the calling party in response to a request from the fraud operator.
6. The method of claim 1, wherein if the call has a fraudulent attribute then the method further includes the steps of connecting the fraudulent call to the called party and collecting information associated with the ongoing fraudulent call.
7. The method of claim 6, wherein said collected information includes information associated with the calling party and the called party.
8. The method of claim 1, wherein if the call has a fraudulent attribute then the method further includes the step of Informing the calling party about the fraudulent call.
9. The method of claim 1, wherein said intelligent network service engine utilizes information previously received from or stored against a legitimate calling party in determining whether the call has a fraudulent attribute.
10. The method of claim 1, wherein said intelligent network service engine need not use information from a legitimate calling party in determining whether the call has a fraudulent attribute.
11. An intelligent network service engine comprising:
a fraud management system capable of performing real time fraud analysis on an originating side of a call stream to determine whether a call has a fraudulent attribute and preventing the connection of the call to a called a called party until the determination is complete. 12. The intelligent network service engine of claim 11, wherein said fraud management system includes a controller that uses at least one fraud analysis algorithm to determine whether the call has a fraudulent attribute.
13. The intelligent network service engine of claim 12, wherein said at least one fraud analysis algorithm can operate in less than 500 milliseconds to determine whether the call has a fraudulent attribute.
14. The intelligent network service engine of claim 11, wherein if the call has a fraudulent attribute then said fraud management system is capable of blocking the fraudulent call.
15. The intelligent network service engine of claim 11, wherein if the call has a fraudulent attribute then said fraud management system is capable of forwarding the fraudulent call to a network announcement system.
16. The intelligent network service engine of claim 11, wherein if the call has a fraudulent attribute then said fraud management system is capable of forwarding the fraudulent call to a fraud operator.
17. The intelligent network service engine of claim 11, wherein if the call has a fraudulent attribute then said fraud management system is capable of connecting the fraudulent call to the called party and collecting information associated with the ongoing fraudulent call.
18. The intelligent network service engine of claim 11, wherein if the call has a fraudulent attribute then said fraud management system is capable of informing the calling party about the fraudulent call.
19. The intelligent network service engine of claim 11, wherein said intelligent network service engine is a service control point.
20. The intelligent network service engine of claim 11, wherein said intelligent network service engine is a home location register.
21. The intelligent network service engine of claim 11, wherein said intelligent network service engine is an INSight Platform.
22. The intelligent network service engine of claim 11, wherein if the call has a fraudulent attribute then said fraudulent call can be associated with a stolen calling card or a stolen mobile phone.
23. The intelligent network service engine of claim 11, wherein if the call has a fraudulent attribute then said fraudulent call can be part of a focused overload attack on an Internet web site.
a switch capable of receiving a call originated by a calling party; and an intelligent network service engine capable receiving a query about the call from said switch, and further capable of using real time fraud management tools to analyze information within the query to determine whether the call has a fraudulent attribute and preventing the connection of the call to a called party until the determination is complete. 25. The system of claim 24, wherein if the call has a fraudulent attribute then said intelligent network service engine is capable of blocking the fraudulent call.
26. The system of claim 24, wherein if the call has a fraudulent attribute then said intelligent network service engine is capable of forwarding the fraudulent call to a network announcement system.
27. The system of claim 24, wherein if the call has a fraudulent attribute then said intelligent network service engine is capable of forwarding the fraudulent call to a fraud operator.
28. The system of claim 24, wherein if the call has a fraudulent attribute then said intelligent network service engine is capable of connecting the fraudulent call to the called party and collecting information associated with the ongoing fraudulent call.
29. The system of claim 24, wherein said calling party originates the call using a wired phone, a wireless phone or an Internet device.
30. The system of claim 24, wherein said intelligent network service engine is a service control point.
31. The system of claim 24, wherein said intelligent network service engine is a home location register.
32. The system of claim 24, wherein said intelligent network service engine is an INSight Platform.
33. The system of claim 24, wherein said system is a wireless communications network, a wired communications network or an Internet network.
34. The system of claim 24, wherein said intelligent network service engine utilizes information previously received from or stored against a legitimate calling party in determining whether the call has a fraudulent attribute.
35. The system of claim 24, wherein said intelligent network service engine need not use information from a legitimate calling party in determining whether the call has a fraudulent attribute.
CROSS REFERENCE TO RELATED APPLICATION This application is related to U.S. patent application Ser. No. 09/795376 filed on Feb. 26, 2001 and entitled �SYSTEM, INTELLIGENT NETWORK SERVICE ENGINE AND METHOD FOR INFORMING MONITORING PERSONNEL ABOUT AN ONGOING FRAUDULENT CALL OR AN ATTEMPTED FRAUDULENT CALL� which is incorporated by reference herein.
The present invention relates in general to the communications field and, in particular, to a system, intelligent network service engine and method capable of performing real time fraud analysis on an originating side of a call stream to determine whether or not a call is a fraudulent call before the call is connected to a called party.
Telecommunications fraud is an ever-increasing problem that can be very expensive to communication companies and their customers. Telecommunications fraud can occur in wireline networks, wireless network and Internet networks. For instance, one of the most common telephone fraud schemes occurs when a calling card is stolen, duplicated and distributed to many users. These users then use the stolen calling card to make fraudulent calls. The network operator servicing the calling card eventually becomes aware that the calling card has been stolen and refuses to approve the termination of any calls associated with the stolen calling card. Unfortunately, at this point in time, the costs associated with servicing and terminating all of these fraudulent calls can be very expensive.
Today, telecommunications fraud is typically detected after completion of a fraudulent call by processing network management post event statistics or CDR's (Call Detail Records (billing records)). Generally, the traditional post event fraud processing of a call is done by sending information about the terminated call to a fraud management system which can detect fraudulent attributes and inform an operator about a fraudulent number (or stolen, misused, threatened account) who then manually turns that fraudulent number off at an intelligent network service engine (e.g., service control point, home location register). This process can take 1-48 hours to complete after the termination of the first fraudulent call. Post processing (even very quickly) of call is still performed after a call is terminated which is not desirable since a first fraudulent call can be by itself very expensive. Accordingly, there has been a need for a system, intelligent network service engine and method capable of performing real time fraud analysis on an originating side of a call stream to determine whether or not a call is a fraudulent call before the call is connected to a called party. This need and other needs are satisfied by the system, intelligent network service engine and method of the present invention.
BRIEF DESCRIPTION OF THE INVENTION The present invention includes a system, intelligent network service engine and method capable of performing real time fraud analysis on an originating side of a call stream to determine whether or not a call is a fraudulent call before the call is connected to a called party. In particular, the system includes a switch, capable of receiving a call originated by a calling party and an intelligent network service engine capable of receiving information (e.g., call origination data) about the call from the switch. The intelligent network service engine (e.g., home location register, service control point, INSight platform) then uses real time fraud management tools to analyze the call origination data to determine whether or not the call has a fraudulent attribute before the call is connected to a called party. The system can be configured as a wired communications network, a wireless communications network and/or an Internet network.
FIG. 2 is a block diagram illustrating in greater detail a first embodiment of the system shown in FIG. 1;
FIG. 3 is a block diagram illustrating in greater detail a second embodiment of the system shown in FIG. 1;
FIG. 4 is a block diagram illustrating in greater detail a third embodiment of the system shown in FIG. 1; and
FIG. 5 is a flowchart illustrating the basic steps of a preferred method for detecting a fraudulent call in accordance with the present invention.
DETAILED DESCRIPTION OF THE DRAWINGS Referring to FIGS. 1-5, there are disclosed preferred embodiments of a system 100, intelligent network service engine 102 and method 500 in accordance with the present invention. Although the present invention is described as performing real time fraud analysis on an originating side of a call stream to determine whether or not a call is a fraudulent call, it should be understood that the present invention can also be used to perform real time fraud analysis during a call. Accordingly, the system 100, the intelligent network service engine 102 and the method 500 should not be construed in a limited manner.
Referring to FIG. 1, there is a block diagram illustrating the system 100 which includes the intelligent network service engine (INSE) 102 and a switch 104. Essentially, the switch 104 receives a call 106 originated by a calling party 108 and then forwards a query 110 containing information about the call 106 to the INSE 102. The INSE 102 includes a fraud management system 112 that utilizes real time fraud management tools to analyze the information (e.g., call origination data) within the query 110 and determine whether or not the call 106 has a fraudulent attribute before the call 106 is allowed to be connected to a called party 114.
The fraud management system 112 in determining whether or not the call 106 is a fraudulent call can use real time fraud management tools to compare information in the call origination data to information (e.g., pin number to a calling card) that was previously provided by or stored against a legitimate calling party. Moreover, the fraud management system 112 can determine whether or not the call 106 is a fraudulent call without any previous input from a legitimate call party. For instance, the fraud management system 112 can use the real time fraud management tools to detect a fraudulent call from a mobile phone by determining whether there are any other ongoing calls from the same mobile phone (assume only one call is allowed at a time) The determination that an incoming call 106 can be a fraudulent call or at least a suspected fraudulent call at the origination of a call is very desirable since valuable network resources need not be used to connect a fraudulent call to a called party 114. As such, the fraud management system 112 can even detect an original fraudulent call before terminating that fraudulent call to the called party 114. This is a marked improvement over the state of the art where an original fraudulent call would be terminated to a called party and, then at a later time, the network operator would learn that this call was a fraudulent call and block future fraudulent calls.
The INSE 102 can do a variety of things once an incoming call 106 is determined to be a fraudulent call or at least suspected to be a fraudulent call. For instance, the INSE 102 can forward a response 120 to the switch 104 directing the switch 104 to: (1) block the fraudulent call; (2) forward the fraudulent call to a fraud operator 116; (3) forward the fraudulent call to a network announcement system 118 or at least enable the network announcement system 118 to interact with the calling party 108; or (4) connect the fraudulent call to the called party 114 which would allow the INSE 102 to collect additional information about the ongoing fraudulent call. A more detailed description is provided below about the system 100, the INSE 102 and the various ways the fraud management system 112 can detect a fraudulent attribute in an incoming call 106.
Referring to FIG. 2, there is a block diagram illustrating in greater detail a first embodiment of the system 100. In this embodiment, the system 100 is configured as a wired communications network 100 a, the INSE 102 is configured as a service control point (SCP) 102 a and the switch 104 is configured as a service switching point (SSP) 104 a. For clarity, certain details associated with the system 100 a are known in the industry and as such the description provided below in relation to the system 100 a omits some components not necessary to understand the present, invention.
The calling party 108 a using a land-based phone such as a wired phone or pay phone originates a telephone call 106 a towards a local office switch 202 a that is managed by a local service provider. The local service provider may not service the call 106 a and as such would forward the call 106 a to a long distance switch 104 a (e.g., service switching point (SSP)). The long distance switch 104 a managed by a long distance service provider is programmed to forward information about the telephone call 106 a to the SCP 102 a. In particular, the long distance switch 104 a sends a query 110 a to the SCP 102 a which contains information (e.g., call origination data) about the telephone call 106 a that is analyzed by the fraud management system 112 a to determine whether the call 106 a is or could be fraudulent call before connecting the call 106 a to the called party 114 a (shown in the example to be a wired called party). The SCP 102 a incorporates the fraud management system 112 a which includes a controller 204 a and a database 206 a. In one aspect of the present invention, the fraud management system 112 a analyzes the origination data associated with the incoming call 106 a and information provided earlier by a legitimate calling party to determine whether an incoming call 106 a is or could be a fraudulent call. For example, the fraud management system 112 a can detect or at least suspect that an incoming calling card call is a fraudulent call when a pin number provided by the calling party 108 a does not match a pin number previously provided by a legitimate calling party. In other words, the calling party 108 a in order to make a calling card call 106 a may have to provide a pin number to the SCP 102 a after which the controller 204 a would compare that pin number to a pin number provided earlier by a legitimate calling party. The legitimate pin number would normally be stored in the database 206 a. If the two pin numbers match, then the fraud management system 112 a would allow the switch 104 a to connect the call 106 a to the called party 114 a. Otherwise, if the two pin numbers do not match, then the fraud management system 112 a would suspect that the call 106 a is a fraudulent call and forward the suspected fraudulent call 106 a to a network announcement system 118 (for example). The network announcement system 118 could be configured as an interactive voice response (IVR) system 118 a which could request that the calling party 108 a provide a correct pin number or other validation information before allowing the call 106 a to be connected to the called party 114 a. In another example, the legitimate calling party can provide the fraud management system 112 a with guidelines on the acceptable use of their calling card. For instance, the legitimate calling party may only want their calling card to be used to make calls to potential called parties located in specific calling areas associated with telephone area codes 214 and 817. And, if the fraud management system 112 a subsequently receives origination data from a calling card call 106 a that includes destination information of a called party 114 a that is located in a calling area not associated with area codes 214 and 814, then that call 106 a may be considered a fraudulent call. Prior to connecting the call 106 a to the called party 114 a, the fraud management system 112 a may forward the suspected fraudulent call 106 a to a fraud operator 116 a. The fraud operator 116 a could interact with and try to obtain validation information from the suspected fraudulent calling party 108 a that would enable the call 106 a to be connected to the called party 114 a if it is a legitimate call (e.g., a call to an area outside of area codes 214 or 817).
Of course, the legitimate calling party can provide the fraud management system 112 a with a wide variety of guidelines on the acceptable use of their calling card. For instance, the legitimate calling party may request that the calling card be used to make calls in specific locations, to make calls during certain days or periods of time, or to make a certain number of calls during a certain period of time . . . And, if the fraud management system 112 a subsequently receives origination data of a calling card call 106 a that contains data conflicts with guidelines, then that call 106 a would be suspected of being a fraudulent call.
In another aspect of the present invention, the fraud management system 112 a can use real time fraud management tools to determine whether the call 106 a is or could be a fraudulent call without any previous input from a legitimate calling party. For example, the fraud management system 112 a can detect or at least suspect that an incoming call is a fraudulent call when there is another ongoing call using the same calling card if the number of simultaneous calls exceeds the specified limit. In any case, the fraudulent management system 112 a can determine whether an incoming call 106 a is fraudulent or suspected to be fraudulent in around 250-500 milliseconds, where 250 milliseconds is the engineering goal and 500 milliseconds is the field survivable worst case.
The fraud management system 112 a can do a variety of things once an incoming call 106 a is determined to be a fraudulent call or at least suspected to be a fraudulent call. As described above, the fraud management system 112 a can forward a response 120 a to the SSP 104 a directing the SSP 104 a to: (1) block the fraudulent call; (2) forward the fraudulent call to a fraud operator 116 a; (3) forward the fraudulent call to a network announcement system 118 a (e.g., interactive voice response (IVR) system) or at least enable the IVR 118 a to interact with the calling party 108 a; or (4) connect the fraudulent call to the called party 114 a which would allow the fraud management system 114 a to collect additional information about the ongoing fraudulent call.
It should be understood that the SSP 104 a can perform the same calculations and translations as the SCP 102 a to determine whether the telephone call 106 a has a fraudulent attribute. But, the SSP 104 a typically does not perform complicated calculations and translations, because, a relatively small number of SCPs 102 a can be more easily and efficiently programmed with the real time fraud management tools. It should also be understood that the local service provider could also offer the services of the present invention to their customers by enhancing their own switch 202 a or SCP (not shown) to include a fraud management system 112 a. Referring to FIG. 3, there is a block diagram illustrating in greater detail a second embodiment of the system 100. In this embodiment, the system 100 is configured as a wireless communications network 100 b, the INSE 102 is configured as a home location register (HLR) 102 b and the switch 104 is configured as a mobile switching center (MSC) 104 b. For clarity, certain details associated with the system 100 b are known in the industry and as such the description provided below in relation to the system 100 b omits some components not necessary to understand the present invention.
The calling party 108 b uses a mobile phone to originate the telephone call 106 b towards a base station controller (BSC) 302 b that provides wireless service to mobile subscribers located in one or more cells of the wireless communications network 10 b. The BSC 302 b then forwards the wireless call 106 b to a MSC 104 b. The MSC 104 b is programmed to forward information about the wireless call 106 b to the HLR 102 b. In particular, the MSC 104 b sends a query 110 b to the HLR 102 b which contains information (e.g., call origination data) about the wireless call 106 b that is analyzed by the fraud management system 112 b to determine whether the call 106 b is or could be a fraudulent call before connecting the call 106 b to the called party 114 b (shown in this example to be a wireless called party). The HLR 102 b incorporates the fraud management system 112 b which includes a controller 204 b and a database 206 b. In one aspect of the present invention, the fraud management system 112 b analyzes the origination data associated with the incoming wireless call 106 b and information provided earlier by a legitimate calling party to determine whether an incoming wireless call 106 b is or could be a fraudulent call. In particular, the legitimate calling party can provide the fraud management system 112 b with guidelines on the acceptable use of their mobile phone. For instance, the legitimate calling party may provide a guideline that the mobile phone is to be used to originate calls only from a specific geographical area such as Texas. And, if the fraud management system 112 b subsequently receives origination data of a wireless call 106 b which indicates that the calling party 108 b is not La located in Texas, then that call 106 b may be considered a fraudulent call. If call 106 b is determined to be a fraudulent call, then the fraud management system 112 b could instruct the MSC 104 b to forward the fraudulent call 106 b to a fraud operator 116 b (for example). The fraud operator 116 b could then interact with and obtain validation information from the calling party 108 b that would enable the wireless call 106 b to be connected to the called party 114 b. Of course, the legitimate calling party can provide the fraud management system 112 b with a wide variety of guidelines on the acceptable use of their mobile phone. For instance, the legitimate calling party may request that the mobile phone be used to make calls from specific locations, to call people in specific locations, to call during certain days or certain periods of time, or to make a certain number of calls in one period of time . . . And, if the fraud management system 112 b subsequently receives origination data of a wireless call 106 b that contains data that indicates any of these guidelines are not satisfied, then that call 106 a would be suspected of being a fraudulent call.
In another aspect of the present invention, the fraud management system 112 b can use real time fraud management tools to determine whether the wireless call 106 b is or could be a fraudulent call without any previous input from a legitimate calling party. For example, the fraud management system 112 b can detect or at least, suspect that an incoming call 106 b is a fraudulent call when there already is an ongoing call having the same mobile identification number as the present mobile phone. In other words, one of these calls is fraudulent. If the fraudulent management system 112 b detects multiple ongoing wireless calls originating from what appears to be the same mobile phone (e.g., cloned mobile phone), then the fraud management system 112 b can simply block the termination of the fraudulent call. Alternatively, the, fraud management system 112 b could have the fraudulent call 106 b connected to the called party 114 b and then collect additional information about the ongoing fraudulent call. The fraud management system 112 b could even provide law enforcement personnel with information about the fraudulent call, the fraudulent calling party and the called party.
As above, the fraud management system 112 b can do a variety of things once an incoming wireless call 106 b is determined to be a fraudulent call or at least suspected to be a fraudulent call. The fraud management system 112 b can forward a response 120 b to the MSC 104 b directing the MSC 104 b to: (1) block the fraudulent call; (2) forward the fraudulent call to a fraud operator 116 b; (3) forward the fraudulent call to a network announcement system 118 b (e.g., interactive voice response (IVR) system) or at least enable the IVR 118 b to interact with the calling party 108 b; or (4) connect the fraudulent call to the called party 114 b which would allow the fraud management system 112 b to collect additional information about the ongoing fraudulent call.
In either aspect of the present invention, the fraudulent management system 112 a can determine whether an incoming wireless call 106 b is fraudulent or suspected to be fraudulent in around 250-500 milliseconds, where 250 milliseconds is the engineering goal and 500 milliseconds is the field survivable worst case. It should also be understood that the MSC 104 b can incorporate a fraud management system 112 b instead of the HLR 102 b. Referring to FIG. 4, there is a block diagram illustrating in greater detail a third embodiment of the system 100. In this embodiment, the system 100 is configured as a Internet network 100 c, the INSE 102 is configured as a InSight platform 102 c and the switch 104 is configured as an Internet service provider (ISP) 104 c. For clarity, certain details associated with the system 100 care known in the industry and as such the description provided below in relation to the system 100 c omits some components not necessary to understand the present invention.
The calling party 108 c uses a computer (or mobile phone, personal digital assistant . . . ) to originate an Internet call 106 c or any Internet related communication towards an ISP 104 c that provides Internet service to the calling party 108 c. Here, call is used in a broad sense. The ISP 104 c then forwards information about the Internet call 106 c to the INSight platform 102 c. In particular, the ISP 104 c sends a query (not shown) to the INSight platform 102 c which contains information (e.g., call origination data) about the Internet call 106 c that is analyzed by the fraud management system 112 c to determine whether the call 106 c is or could be a fraudulent call before connecting the Internet call 106 c to a called party 114 c (e.g., web site). As shown, the called party 114 c is serviced by another ISP 402 which is connected to ISP 104 c by the Internet 404. The INSight platform 102 c incorporates the fraud management system 112 c which includes a controller 204 c and a database 206 c. In one aspect of the present invention, the fraud management system 112 c analyzes the call origination data associated with the incoming Internet call 106 c and possibly other data to determine whether the call 106 c is or could be a fraudulent call. For an example of fraud prevention applied at the terminating end, the fraud management system 112 c can use real time fraud management tools to analyze the call origination data of the Internet call 106 c and determine whether this call 106 c is just one of many similar Internet calls that may be bombarding a particular web site with queries in an attempt to shutdown that web site. The attacked web site is shown as being associated with the called party 114 c. In particular, the fraud management system 112 c may determine from the origination data a domain name, an Internet Protocol (IP) address and/or an originating destination that is responsible for the attack on the web site of the called party 114 c. Upon determining the existence or possible existence of a fraudulent Internet call 106 c, the fraud management system 112 c could interact with and direct the ISP 104 c to block this and any future fraudulent Internet calls from calling party 108 c. As in the other embodiments, the fraud management system 112 c can do a variety of things once an incoming Internet call 106 c is determined to be a fraudulent call or at least suspected to be a fraudulent call. For instance, the fraud management system 112 b can do the following: (1) block the fraudulent call; (2) forward the fraudulent call to an on-line fraud operator (not shown); (3) forward the fraudulent call to a network announcement system (not shown); or (4) connect the fraudulent call to the called party 114 c or destination and then collect additional information about the ongoing fraudulent call.
Referring to FIG. 5, there is a flowchart illustrating the basic steps of a preferred method 500 for detecting a fraudulent call in accordance with the present invention. Beginning at step 502, the INSE 102 receives a query 110 (e.g., TCAP origination signal) about a call originated by a calling party 108. As described above, the INSE 102 can be configured as a SCP 102 a, a HLR 102 b and/or an INSight platform 102 c. Moreover, the INSE 102 can be known as an Intelligent Network Platform (INP), an Application Server (AS) or as a Software Enabled Advanced Logic Routing Method (SEALRM).
At steps 504 and 506, the INSE 102 uses real time fraud management tools to analyze (step 504) the call origination data associated with the query 110 and determine (step 506) whether the call 106 has a fraudulent attribute prior to connecting the call 106 to the called party 114 or destination. The fraud management tools include at least one fraud analysis algorithm that can operate for around 250-500 milliseconds to determine whether the call 106 has a fraudulent attribute. As such, the fraud management system 112 operates in real time since 250-500 milliseconds is typically the longest duration the INSE 102 would need to complete its other translation work on the incoming call 106. If the call 106 is not a fraudulent call or a suspected fraudulent call, then at step 508, the fraud management system 112 and the INSE 102 instruct the switch 104 to connect the call 106 to the called party 114. Otherwise, if the call 106 is a fraudulent call or a suspected fraudulent call, then the fraud management system 112 can do a variety of things as described below with respect to steps 510-524.
At step 510, the fraud management system 112 can operate to block the fraudulent call 106 or the suspected fraudulent call 106. The blocking of an original fraudulent call 106 is a marked improvement over the state of the art in which an original fraudulent call would normally be terminated to a called party and, then at a later time, the network operator would learn that this call was a fraudulent call and block future fraudulent calls.
At steps 512 and 514, the fraud management system 112 can operate to forward (step 512) the fraudulent call 106 or the suspected fraudulent call 106 to a network announcement system 118. The network announcement system 118 can be configured as an Interactive Voice Response (IVR) system or an IP-SRP which is part of an Intelligent Network. The IVR can use pre-programmed messages to interact with the calling party 108 in an attempt to obtain (step 514) validation information from the calling party 108. If the calling party 108 does not correctly answer the requests from the IVR then the call 106 may be blocked. At steps 516 and 518, the fraud management system 112 can forward (step 516) the fraudulent call 106 or the suspected fraudulent call 106 to a fraud operator 116. The fraud operator 116 can interact with the calling party 108 in an attempt to obtain (step 518) validation information from the calling party 108. If the calling party 108 does not correctly answer the requests of the fraud operator 116 then the call 106 may be blocked.
At steps 520 and 522, the fraud management system 112 could connect (step 520) the fraudulent call 106 to the called part 114 and then collect (step 522) information about the ongoing fraudulent call 106, the calling party 108 and the called party 114. Following is a brief list of the possible data that could be collected by the fraud management system 112:
Source address (IP address, URL, Telephone/Station Number etc . . . ) Destination address (IP address, URL, Telephone Number etc . . . ) Credit card number Calling card number Day/Date/Time information Source geographic information Destination geographic information Call duration Call type Forwarded to address Call treatment (at destination)
The fraud management system 112 could even provide law enforcement personnel with information about the fraudulent call, the fraudulent calling party and the called party.
Lastly, at step 524, the fraudulent management system 112 could inform the fraudulent calling party 108 that the fraudulent call 106 or the suspected fraudulent call 106 has been marked as fraudulent and placed on a fraud list. The calling party 108 may also be informed that they should be expecting a call from a fraud operator 116 or should call a specific number to talk with a fraud operator 116 to try and re-instate their call privileges. As shown, step 524 would likely follow steps 514, 518 and 522.
From the foregoing, it can be readily appreciated by those skilled in the art that the present invention provides a system, intelligent network service engine and method capable of performing real time fraud analysis on an originating side of a call stream to determine whether or not a call is a fraudulent call before the call is connected to a called party. As disclosed, the present invention can be implemented within a wired communications network, a wireless communications network and/or an Internet network.
Citations de brevets Brevet cit� Date de d�p�t Date de publication D�posant TitreUS5434920 *27 ao�t 199318 juil. 1995At&T Corp.Secure telecommunicationsUS5495521 *12 nov. 199327 f�vr. 1996At&T Corp.Method and means for preventing fraudulent use of telephone networkUS5566234 *19 sept. 199515 oct. 1996Mci Communications CorporationMethod for controlling fraudulent telephone callsUS5907602 *29 mars 199625 mai 1999British Telecommunications Public Limited CompanyDetecting possible fraudulent communication usageUS6320947 *14 sept. 199920 nov. 2001Satyam Enterprise Solutions LimitedTelephony platform and method for providing enhanced communication services* Cit� par l'examinateur R�f�renc� par Brevet citant Date de d�p�t Date de publication D�posant TitreUS7127233 *31 juil. 200324 oct. 2006Metro One Telecommunications, Inc.Technique for controlling fraudulent use of a telecommunication service including information assistanceUS7406159 *15 juil. 200429 juil. 2008TekelecMethods, systems, and computer program products for automatically populating signaling-based access control databaseUS8380165 *22 oct. 201019 f�vr. 2013Sprint Communications Company L.P.Identifying a cloned mobile device in a communications networkWO2011080638A110 d�c. 20107 juil. 2011Turkcell Teknoloji Arastirma Ve Gelistirme Anonim SirketiIllegal carrier detection platform and method* Cit� par l'examinateurClassifications Classification aux �tats-Unis706/50, 379/114.14 Classification internationaleH04L29/06, G06N5/02, H04Q3/00, H04W12/12, H04W4/24 Classification coop�rativeH04Q2213/13139, H04W4/24, H04M2215/016, H04L63/1416, H04M15/47, H04Q3/0029, H04M15/90, H04L63/1441, H04M2215/2026, H04Q2213/13256, H04M2215/0148, H04W12/12, H04Q2213/13345, H04Q2213/13274 Classification europ�enneH04M15/90, H04W4/24, H04M15/47, H04L63/14A1, H04L63/14D, H04Q3/00D3Faire pivoterImage d'origineAccueil Google - Plan du site - T�l�chargements par lot sur l'USPTO - R�gles de confidentialit� - Conditions d'utilisation - � propos de Google�Brevets - Envoyer des commentairesDonn�es fournies par IFI CLAIMS Patent Services©2012 Google