The International University of Engineering and Technology has launched cybersecurity research to develop algorithms for detecting network anomalies using artificial intelligence. The project is being implemented at the Software Engineering Department within the framework of the Zhas Galim state grant financing program for 2025-2027. It aims to improve corporate and government organizations` digital infrastructure reliability.

Modern cyber attacks are becoming more complex, which requires the development of new protection methods that can adapt to changing conditions. The developed algorithms will automatically detect threats without the need for constant updating of signature databases and manual configuration. The project will use modern approaches to machine learning, including autoencoders, self-learning, federated learning, and explicable artificial intelligence (XAI), which will improve the accuracy of threat detection and make the algorithms more transparent to users. International cooperation, including Purdue University (USA) and Kazakhstan Institute of Information and Computing Technologies, is essential to the work.

The project`s results are expected to find practical application in various industries, such as finance, energy, and telecommunications. Developing and implementing new anomaly detection algorithms will increase the cyber protection of corporate networks, reduce operational risks, and strengthen Kazakhstan`s technological independence in information security.