Call screening service for communication devices
One example method of operation may include collecting call metric data over a predefined period of time for identified calls, querying the call metric data to identify whether one or more call filtering criteria parameters require changes, determining one or more call filtering criteria parameters require changes based on a deviation from one or more expected call metric data values included in the call metric data, modifying one or more of the call filtering criteria parameters, and updating an active call scam model stored on a call processing server based on the one or more call filtering parameters.
1. A method comprising:
in response to a SIP INVITE message being received by a call processing server before ringing an end-user device, modifying one or more call filtering criteria parameters of a call scam model being executed by the call processing server based on a deviation identified in the one or more call filtering criteria parameters; and
updating the call scam model based on the one or more call filtering criteria parameters that have been modified;
wherein the call scam model includes a first call scam model average score and a second call scam model average score based on different call metric data.
2. The method of claim 1 , wherein the updating of the call scam model occurs every 1-10 minutes.
3. The method of claim 1 , wherein the updating of the call scam model further comprises:
updating one or more scam call data tables stored in the call processing server.
4. The method of claim 1 , comprising:
identifying the deviation based on call metric data being collected during a predefined period of time with a plurality of calls occurring every 30-90 days.
5. The method of claim 1 , wherein the call metric data comprises one or more of:
a number of calls per day,
a percentage of calls that were blocked per day,
an historic percentage of calls that were blocked on one or more previous days,
a timestamp of blocked calls,
phone number occurrences of callers,
phone number occurrences of callees, and
local exchange routing guide (LERG) information.
6. The method of claim 1 , comprising:
identifying the deviation based on a difference between an actual value of call metric data and an expected value for the call metric data exceeding.
7. The method of claim 1 , comprising:
collecting call metric data over a predefined period of time for a plurality of calls to a plurality of call processing servers, each with unique call metric data.
8. An apparatus comprising:
a processor that, when executing instructions stored in an associated memory, is configured to:
in response to a SIP INVITE message being received by a call processing server before ringing an end-user device, modify one or more call filtering criteria parameters of a call scam model being executed by the call processing server based on a deviation identified in the one or more call filtering criteria parameters; and
update the call scam model based on the one or more call filtering criteria parameters that have been modified;
wherein the call scam model includes a first call scam model average score and a second call scam model average score based on different call metric data.
9. The apparatus of claim 8 , wherein the update of the call scam model occurs every 1-10 minutes.
10. The apparatus of claim 8 , wherein when the processor updates the call scam model, the processor is further configured to:
update one or more scam call data tables stored in the call processing server.
11. The apparatus of claim 8 , wherein the processor is configured to:
identify the deviation based on call metric data being collected at a predefined period of time with a plurality of calls that occur every 30-90 days.
12. The apparatus of claim 8 , wherein the call metric data comprises one or more of:
a number of calls per day,
a percentage of calls that were blocked per day,
an historic percentage of calls that were blocked on one or more previous days,
a timestamp of blocked calls,
phone number occurrences of callers,
phone number occurrences of callees, and
local exchange routing guide (LERG) information.
13. The apparatus of claim 8 , wherein the processor is configured to:
identify the deviation based on a difference between an actual value of call metric data and an expected value for the call metric data exceeding.
14. The apparatus of claim 8 , wherein the processor is configured to:
collect call metric data over a predefined period of time for a plurality of calls to a plurality of call processing servers each with unique call metric data.
15. A non-transitory computer-readable storage medium configured to store instructions that, when executed by a processor, cause the processor to perform:
in response to a SIP INVITE message being received by a call processing server before ringing an end-user device, modifying one or more call filtering criteria parameters of a call scam model being executed by the call processing server based on a deviation identified in the one or more call filtering criteria parameters; and
updating the call scam model based on the one or more call filtering criteria parameters that have been modified;
wherein the call scam model includes a first call scam model average score and a second call scam model average score based on different call metric data.
16. The non-transitory computer-readable storage medium of claim 15 , wherein the updating of the call scam model occurs every 1-10 minutes.
17. The non-transitory computer-readable storage medium of claim 15 , wherein the updating of the call scam model further comprises:
updating one or more scam call data tables stored in the call processing server.
18. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions further cause the processor to perform:
identifying the deviation based on call metric data being collected during a predefined period of time with a plurality of calls occurring every 30-90 days.
19. The non-transitory computer-readable storage medium of claim 15 , wherein the call metric data comprises one or more of:
a number of calls per day,
a percentage of calls that were blocked per day,
an historic percentage of calls that were blocked on one or more previous days,
a timestamp of blocked calls,
phone number occurrences of callers,
phone number occurrences of callees, and
local exchange routing guide (LERG) information.
20. The non-transitory computer-readable storage medium of claim 15 , the instructions further cause the processor to perform:
identifying the deviation based on a difference between an actual value of call metric data and an expected value for the call metric data exceeding.