Telecommunication fraud prevention system and method based on big data and machine learning

A machine learning and big data technology, applied in the field of information security, can solve the problems of low cost, early warning delay, governance and combating telecom fraud difficulties, etc., to achieve the effect of simple algorithm

Inactive Publication Date: 2017-07-21
INST OF SOFTWARE APPL TECH GUANGZHOU & CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

In this patented technology, it helps detect if someone has been deceived into sending false messages on their phones during an online communication session without being detected. It uses advanced algorithms to analyze emails from different sources such as social media sites, email addresses, etc., making sure they don’t contain any suspicious characters like spamming words or fake news about them. Additionally, there may exist similar methods used at home (like credit card verification), allowing authorities to quickly respond accordingly. Overall, these technical features improve efficiency and effectiveness over existing systems while reducing potential harm caused due to improperly identified attacks.

Problems solved by technology

Technological Problem addressed in this patented text relates to improving upon identifying potential threats (fragrances), particularly when dealing with anonymous calls made over internet protocol networks where there may exist multiple ways to deceive people into false accounts. Existing prior art solutions involve either monitoring network activity or triggering alarms based solely on caller ID data without considering any specific factors like location.

Method used

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  • Telecommunication fraud prevention system and method based on big data and machine learning
  • Telecommunication fraud prevention system and method based on big data and machine learning
  • Telecommunication fraud prevention system and method based on big data and machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] Such as figure 1 As shown, the present invention provides a system for preventing telecom fraud based on big data and machine learning, including:

[0060] The mobile terminal is used to conduct fraud detection and judgment on the current telecommunications data through predetermined constraint rules when receiving a text message or an incoming call message, and use a machine learning algorithm to detect whether it is a telecommunications fraud. If the detection result is determined to be a telecommunications fraud, the The fraudulent data information is uploaded to the big data analysis terminal;

[0061] The big data analysis terminal is used for real-time statistics of fraud data information uploaded and reported from the mobile terminal, and sends fraud warning information to the fraud blocking management terminal for bank card accounts or / and phone numbers whose number of reports exceeds a certain threshold;

[0062] The fraud blocking management terminal is used ...

Embodiment 2

[0106] Such as Figure 5 As shown, a method for preventing telecom fraud based on big data and machine learning of the present invention includes:

[0107] When the mobile terminal receives a text message or an incoming call message, it conducts fraud detection and judgment on the current telecommunications data through predetermined constraint rules, and uses a machine learning algorithm to detect whether it is a telecommunications fraud. If the detection result is determined to be a telecommunications fraud, the fraudulent data will be The information is uploaded to the big data analysis terminal;

[0108] The big data analysis terminal counts the fraud data information uploaded and reported from the mobile terminal in real time, and sends fraud warning information to the fraud blocking management terminal for the bank card account number or / and phone number whose number of reports exceeds a certain threshold;

[0109] The fraud blocking management end takes corresponding m...

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PUM

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Abstract

The invention discloses a telecommunication fraud prevention system and method based on big data and machine learning. The system comprises a mobile terminal, a big data analysis terminal and a fraud interdiction governance terminal, wherein the mobile terminal is used for performing fraud detection determination on current telecommunication data according to predetermined constraint rules when receiving a short message or an incoming call message, a machine learning algorithm is adopted to detect whether the telecommunication data is a telecommunication fraud, and if the detection result is that the telecommunication data is determined as a telecommunication fraud, fraud data information is uploaded to the big data analysis terminal; the big data analysis terminal is used for performing real-time statistics on the fraud data information uploaded and reported from the mobile terminal and sending fraud early-warning information to the fraud interdiction governance terminal according to a bank card account or/and a phone number with the number of received reports exceeding a certain threshold value; and the fraud interdiction governance terminal is used for taking corresponding measures in time to interdict occurrence of a telecommunication fraud event when receiving the fraud early-warning information. The system can unite the mobile terminal, an operator, a public security institution, a bank and other institutions, quick and effective prevention can be realized, and the telecommunication fraud can be cracked down in time.

Description

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Claims

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Application Information

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Owner INST OF SOFTWARE APPL TECH GUANGZHOU & CHINESE ACAD OF SCI
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