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Data leaks can cost companies dearly. Unintentional access to customer data, for example, can quickly result in horrendous fines - the keyword here is data protection. Not to mention the high loss of image and public trust. Numerous examples from the recent past show how important it is for companies to arm themselves against data leaks. Internal data leaks can be caused by industrial espionage, internal data theft or hacked employee accounts, for example.
According to Statista, a data leak costs companies in Germany an average of 4.5 million euros. It takes around 160 days to close it. Early detection speeds up the process and reduces costs - ideally, data theft can be avoided altogether. We developed an early detection system against data leaks for an international mobile communications provider that uses AI to reliably identify unusual behavior in SQL queries. The aim was to detect possible unwanted data leaks in good time so that countermeasures can be taken quickly.
The development team - consisting of data engineers and data scientists - opted for a machine learning approach in which the statistical distribution of SQL activities on the data warehouse is analyzed and deviating behaviour is displayed. The data analysis and the AI algorithm form the basis of the early warning system. Pre-processing of all data was necessary for the modeling - in this case over 1.5 billion data records with a data volume of around 3 terabytes. In order to be able to process this large amount of information, a powerful cloud platform was implemented with the Data Platform. The SQL activities were then classified, the normal behavior analyzed and various criteria for the evaluation determined. The processed data was used to train the AI. Deviations from normal behavior are displayed and evaluated according to a predefined points system.




The data leak early detection system was explicitly adapted to the customer's needs and wishes. Conspicuous behavior in SQL data queries is displayed in good time so that our customer can reliably check whether it is an internal data leak. In addition to improved protection against data theft, the solution offers increased transparency in database activities and IT management can be optimized accordingly. The program code has become the property of the customer so that internal IT specialists can use it freely.
Customer benefits
- Detection and prevention of data theft and industrial espionage
- Avoidance of loss of image and trust
- Avoidance of fines and loss of sales
- Optimization of existing processes
- Transparency in data movements
- Strengthening employees' skills in handling sensitive data
The details
For whom suitable
For all companies that use sensitive data in their databases and have their own IT department.
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