This study is devoted to the urgent task of developing effective and secure cryptographic solutions for Internet of Things (IoT) systems, where devices operate in conditions of limited computing power, memory and energy consumption. Against the background of the rapid proliferation of Embedded Systems (ESP32) microcontroller-based IoT devices and growing cybersecurity threats, a systematic analysis of hardware and software encryption methods is being conducted. The article examines the implementation of cryptographic protection at the microcontroller level in IoT networks, with a special focus on runtime, energy efficiency, and usage in conditions of limited hardware resources. The fundamental difference between the implemented and described programs is the absence of external libraries, which allows it to be implemented on any type of computer, up to microcontrollers. The program's algorithm is adapted for microcontrollers (ESP32) and combines an elliptic curve-based key generation algorithm with machine learning to detect attacks in real time. The key exchange procedure is implemented using the ECDH (Elliptic Curve Diffie-Hellman) protocol, a Diffie-Hellman protocol for secure key exchange based on elliptical curves using the Micro-ECC library. Neural networks were used for machine learning. 

TASHTAY B.A.

Master's degree, PhD student, department of information security, L.N. Gumilyov Eurasian national university, Astana, Kazakhstan

Е-mail: 93bahti93@gmail.com, https://orcid.org/0000-0003-4952-369X

KONYRKHANOVA A.A.

PhD, acting associate professor, department of information security, L.N. Gumilyov Eurasian national university, Astana, Kazakhstan,

E-mail: konyrkhanova_a@enu.kz, https://orcid.org/0000-0002-4901-8901

ATANOV S.K.

Doctor of technical sciences, professor, acting professor, department of computer and software engineering, L.N. Gumilyov Eurasian national university, Astana, Kazakhstan

E-mail: atanov5@mail.ru, https://orcid.org/0000-0003-2115-7130

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microcontroller, elliptical curves, key generation, cryptographic information protection, digital security, neural networks, internet of things (IoT)