Neural Network Method of Analysing Sensor Data to Prevent Illegal Cyberattacks
Vladov S. Jotsov V. Sachenko A. Prokudin O. Ostapiuk A. Vysotska V.
September 2025Multidisciplinary Digital Publishing Institute (MDPI)
Sensors
2025#25Issue 17
This article develops a method for analysing sensor data to prevent cyberattacks using a modified LSTM network. This method development is based on the fact that in the context of the rapid increase in sensor devices used in critical infrastructure, it is becoming an urgent task to ensure these systems’ security from various types of attacks, such as data forgery, man-in-the-middle attacks, and denial of service. The method is based on predicting normal system behaviour using a modified LSTM network, which allows for effective prediction of sensor data because the F1 score = 0.90, as well as on analysing anomalies detected through residual values, which makes the method highly sensitive to changes in data. The main result is high accuracy of attack detection (precision = 0.92), achieved through a hybrid approach combining prediction with statistical deviation analysis. During the computational experiment, the developed method demonstrated real-time efficiency with minimal computational costs, providing accuracy up to 92% and recall up to 89%, which is confirmed by high AUC = 0.94 values. These results show that the developed method is effectively protecting critical infrastructure facilities with limited computing resources, which is especially important for cyber police.
cyber police , cyberattacks , loss function , neural network , residuals , sensor system , sensory data
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Department of Scientific Activity Organization, Kharkiv National University of Internal Affairs, 27, L. Landau Avenue, Kharkiv, 61080, Ukraine
Department of Information Systems and Technologies, University of Library Studies and Information Technologies, 119, Tsarigradsko Shose, Sofia, 1784, Bulgaria
Department of Cybersecurity, International Information Technology University, 34A, Manas Street, Almaty, 050000, Kazakhstan
Research Institute for Intelligent Computer Systems, West Ukrainian National University, 11, Lvivska Street, Ternopil, 46009, Ukraine
Department of Teleinformatics, Casimir Pulaski Radom University, 29, Malczewskiego Street, Radom, 26-600, Poland
Department of Organization of Educational and Scientific Training, Kharkiv National University of Internal Affairs, 27, L. Landau Avenue, Kharkiv, 61080, Ukraine
Lviv State University of Life Safety, Lviv, 79000, Ukraine
Information Systems and Networks Department, Lviv Polytechnic National University, 12, Bandera Street, Lviv, 79013, Ukraine
Department of Scientific Activity Organization
Department of Information Systems and Technologies
Department of Cybersecurity
Research Institute for Intelligent Computer Systems
Department of Teleinformatics
Department of Organization of Educational and Scientific Training
Lviv State University of Life Safety
Information Systems and Networks Department
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