Thoughts on the study and judgment of telecommunications fraud cases in the big data environment

In recent years, the public security organs have intensified their efforts to crack down on telecommunications fraud and achieved remarkable results. However, the number of such cases continues to grow, and the criminal methods are changing rapidly, the spatial span is large, and the trend of gangs is obvious. It is difficult to recover stolen goods, and the case-solving model is difficult to replicate. In order to solve the case, investigators often need to fight across regions for a long time.

Mininglamp Data has developed the SCOPA system with big data association relationship mining technology as the core, which integrates and associates massive multi-source heterogeneous data and displays the entire data into an easy-to-understand point-edge relationship diagram. Data in any department of the public security agency and any server can be integrated through the SCOPA system for unified retrieval, correlation, analysis and judgment on the same interface. At present, this system has been widely implemented and has achieved a lot of practical results. This system has the following three major advantages when applied to the research, judgment and detection of telecommunications fraud cases:

1. It greatly improves the efficiency of clue research and judgment, effectively shortens the cycle of solving cases, and seizes the opportunity for action.

When the detection of telecommunications fraud is in a deadlock due to criminals' counter-investigation methods, it is often necessary to comprehensively integrate the criminals' calls, text messages, Internet access, transfers and other all-dimensional behavioral clues to find a breakthrough. At this time, if all these data are In a fragmented system, the police have to spend a lot of time investigating, and criminals have the opportunity to escape. Utilizing the full relationship network diagram and powerful applications such as full search, correlation analysis, geographical mining, and call order analysis built on this basis, SCOPA can help case investigators locate in just a few minutes what would have taken hours or even days. Clues can only be obtained through investigation work. In addition, SCOPA also supports real-time manual import of new clues discovered in real time during the investigation of specific cases. No matter how complex the data is, whether it is thousands of pages of call records, Internet access records, historical files, or transcript information, it can be entered into the system easily and quickly, and it can be quickly associated with the existing data in the system, allowing new clues to surface.

2. Use a concise graphical interface to restore the complex deductions of real cases and lower the experience threshold for complex research and judgment.

Criminal suspects in telecommunications fraud cases are extremely cunning. Once they find any trouble, they may change their contact information, etc., causing the clues of the investigation to be interrupted. With the help of the SCOPA platform technology, even if one clue is interrupted, you can follow another clue at any time, and it is easier to find clues connected through several layers of relationships. With the technical assistance of SCOPA, police can quickly construct the original appearance of the case in the graphical interface through simple operations. Furthermore, the research and judgment methods used by experienced police officers to deal with various case situations summarized through practice can be deposited in the SCOPA system, allowing another police officer to borrow their wisdom to solve the cases they face across time, regions, and even police types. and questions.

3. Turn passivity into initiative, intelligent early warning and prediction, and prevent criminal behavior.

If there are signs of criminals’ illegal behavior before a fraud case occurs, it can greatly reduce the pressure of case investigation and judgment and play a strong deterrent effect on criminals. Through big data technology, this vision will also become a reality. With the help of full data analysis and algorithm model mining, SCOPA can learn the historical behavioral data of criminals through machine learning technology, summarize the characteristics of their crimes, and issue early warnings when similar characteristics are discovered in the future. For example, the mobile phone bills involved in telecommunications fraud cases are likely to be different from ordinary people's mobile phone bills, showing characteristics such as frequent outgoing calls, few incoming calls, and a large number of hung up calls. The more complete the data, the better it can help the computer restore the true "portraits" of criminals, thereby helping to prevent criminal behavior.

Through the combination and innovation of big data technology and public security business, SCOPA products break through the limitations of the traditional "anti-telecom cybercrime investigation and control platform" and use data fusion, real-time analysis models, large-scale intelligence analysis, etc. The technological advantages make the research and judgment of telecommunications fraud show a new look of efficiency, accuracy and forward-looking. In the era of big data, Mininglamp Data hopes to use the power of technology to help public security agencies bid farewell to traditional policing and move towards truly smart policing.

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