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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Public Health Science (IJPHS) International Journal of Evaluation and Research in Education (IJERE) Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Computer Science and Information Technologies
Moldamurat, Khuralay
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Mechanical Engineering

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About one lightweight encryption algorithm ensuring the security of data transmission and communication between internet of things devices Atanov, Sabyrzhan; Seitkulov, Yerzhan; Moldamurat, Khuralay; Yergaliyeva, Banu; Kyzyrkanov, Abzal; Seitbattalov, Zhexen
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6846-6860

Abstract

In this paper, a new encryption algorithm Twine-Mersenne was developed based on the Twine algorithm with the addition of a random number generator for the dynamic generation of S-boxes. Dynamic generation of random numbers based on the Mersenne Twister helps to increase the cryptographic strength of the proposed algorithm. The algorithm we propose solves the issues of optimizing the costs of computing and energy resources of internet of things (IoT) devices, using a combination of lightweight cryptographic principles and fuzzy logic, and also provides reliable security and intelligent authentication of the mobile application user. The paper also considers the practical implementation of the proposed algorithm based on Arduino ESP32, a device with limited computing resources. In addition to this, fuzzy logic has found its practical application in the field of intelligent user authentication in developed mobile applications based on Arduino Studio for mobile cellular applications. As a result, the proposed lightweight encryption algorithm has proven itself to be an effective tool in ensuring the security of data transmission and communication between IoT devices.
Enhancing cryptographic protection, authentication, and authorization in cellular networks: a comprehensive research study Moldamurat, Khuralay; Seitkulov, Yerzhan; Atanov, Sabyrzhan; Bakyt, Makhabbat; Yergaliyeva, Banu
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp479-487

Abstract

This research article provides an extensive analysis of novel methods of cryptographic protection as well as advancements in authentication and authorization techniques within cellular networks. The aim is to explore recent literature and identify effective authentication and authorization methods, including high-speed data encryption. The significance of this study lies in the growing need for enhanced data security in scientific research. Therefore, the focus is on identifying suitable authentication and authorization schemes, including blockchain-based approaches for distributed mobile cloud computing. The research methodology includes observation, comparison, and abstraction, allowing for a comprehensive examination of advanced encryption schemes and algorithms. Topics covered in this article include multi-factor authentication, continuous authentication, identity-based cryptography for vehicle-to-vehicle (V2V) communication, secure blockchain-based authentication for fog computing, internet of things (IoT) device mutual authentication, authentication for wireless sensor networks based on blockchain, new secure authentication schemes for standard wireless telecommunications networks, and the security aspects of 4G and 5G cellular networks. Additionally, in the paper a differentiated authentication mechanism for heterogeneous 6G networks blockchain-based is discussed. The findings presented in this article hold practical value for organizations involved in scientific research and information security, particularly in encryption and protection of sensitive data.
Improved unmanned aerial vehicle control for efficient obstacle detection and data protection Moldamurat, Khuralay; Atanov, Sabyrzhan; Akhmetov, Kairat; Bakyt, Makhabbat; Belgibekov, Niyaz; Zhumabayeva, Assel; Shabayev, Yuriy
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp3576-3587

Abstract

The article centers on the research objectives and tasks associated with developing a swarm control system for unmanned aerial vehicles (UAVs) utilizing artificial intelligence (AI). A comprehensive literature review was undertaken to assess the effectiveness of the "swarm" method in UAV management and identify key challenges in this domain. Swarm algorithms were implemented in the MATLAB/Simulink environment for modeling and simulation purposes. The study successfully instantiated and simulated a UAV swarm control system adhering to fundamental principles and laws. Each UAV operates autonomously, following target-swarm principles inspired by the collective behavior of bees and ants. The collective movement and behavior of the swarm are controlled by an AI-based program. The system demonstrated effective obstacle detection and avoidance through computer simulations. Results obtained highlight key features contributing to success, including decentralized autonomy, collective intelligence, UAV coordination, scalability, and flexibility. The deployment of a local radio communication system in UAV swarm control and remote object monitoring is also discussed. The research findings hold practical significance as they enable the effective execution of complex tasks and have potential applications in various fields.
Computer program in sign language for controlling mobile objects and communicating with people Moldamurat, Khuralay; Tulembayeva, Aigul; Ryspaev, Askhat; Belgibekov, Niyaz; Peryakina, Lyudmila; Bakyt, Makhabbat
International Journal of Public Health Science (IJPHS) Vol 14, No 1: March 2025
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v14i1.24544

Abstract

This article emphasizes the need for effective communication methods for people with disabilities, focusing on gestures and finger movements. The study aims to address the communication support gap for this group by creating a specialized Kazakh IT dictionary. It explores practical ways to facilitate communication for people with disabilities through gestures, utilizing computer software for the IT dictionary. The article presents key variables, study design, and data analysis procedures. Results show computer programs effectively enable communication for individuals with disabilities. The study's novelty lies in the IT vocabulary covering gestures, benefiting pedagogy, education, and related fields. Computational linguistics, like automatic language processing and machine translation, enhances communication facilitation for the disabled. Practical recommendations are offered for implementing research findings, improving communication and overall quality of life for people with disabilities. In conclusion, the article stresses the importance of effective communication methods, especially gestures, for the disabled. The IT vocabulary creation through computational linguistics offers innovative ways to enhance communication accessibility, prompting further research.
Intelligent voice control system for UAV with mobile robot Atanov, Sabyrzhan; Moldamurat, Khuralay; Bakyt, Makhabbat; Zinagabdenova, Dariga; Moldamurat, Aibek; Zhumazhanov, Berik; Maidanov, Adil
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp1061-1072

Abstract

The article presents a voice control system for unmanned aerial vehicles (UAVs) and an integrated mobile robot, based on artificial intelligence (AI). The system recognizes voice commands in the Kazakh language, converted into Latin transliteration, providing intuitive control of the UAV and robot. The performance of the system in various scenarios including agriculture, environmental monitoring and search and rescue operations is investigated. The system showed high accuracy of command recognition (95%) and efficient control of the UAV and robot. The proposed system opens up new possibilities for the use of UAVs and robots in various fields, increasing their autonomy, flexibility and ease of use.
Geoinformation system for monitoring forest fires and data encryption for low-orbit vehicles Moldamurat, Khuralay; Bakyt, Makhabbat; Yergaliyev, Dastan; Kalmanova, Dinara; Galymzhan, Anuar; Sapabekov, Abylaikhan
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p58-67

Abstract

This article discusses two important aspects of unmanned aerial vehicles (UAVs): forest fire monitoring and data security for low-orbit vehicles. The first part of the article is devoted to the development of a geographic information system (GIS) for monitoring and forecasting the spread of forest fires. The system uses intelligent processing of aerospace data obtained from UAVs to timely detect fires, determine their characteristics and forecast the dynamics of development. The second part of the article focuses on the problem of high-speed encryption of data transmitted from low-orbit aircraft. An effective encryption algorithm is proposed that ensures high data processing speed and reliable protection of information from unauthorized access. The article presents the results of modeling and analysis of the effectiveness of the proposed solutions.
Active online learning with remote sensing data in higher education Moldamurat, Khuralay; Atanov, Sabyrzhan; Nagymzhanova, Karakat; Spada, Luigi La; Kalmanova, Dinara; Tazhikenova, Sapiya; Zhanzhigitov, Syrym; Zhakupov, Altynbek; Yessilov, Assylkhan; Bakyt, Makhabbat
International Journal of Evaluation and Research in Education (IJERE) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v14i3.30096

Abstract

The increasing popularity of online learning has created a need for effective methods to enhance educational quality. This study addresses this need by developing and evaluating an active online learning model incorporating remote sensing data (RSD). The study included a pedagogical experiment with 181 students divided into control and experimental groups. The model included an interactive database, a web portal with tools for processing and visualizing RSD, and the implementation of active learning methods. Data were collected through testing, analysis of completed projects, and questionnaires. Quantitative and qualitative analysis methods were used to process the data. The pedagogical experiment showed that the model improved students’ average scores, increased the number of students with high levels of knowledge acquisition, and enhanced motivation. Thus, the use of RSD and active learning methods in online education is a promising approach to improve the quality of the educational process and foster students’ digital competence.
AI-Enhanced High-Speed Data Encryption System for Unmanned Aerial Vehicles in Fire Detection Applications Moldamurat, Khuralay; Spada, Luigi La; Zeeshan, Nida; Bakyt, Makhabbat; Kuanysh, Absalyam; Zhanibek, Kazybek bi; Tilenbayev, Alzhan
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.26275

Abstract

Small unmanned aerial vehicles (UAVs) are increasingly used for wildfire detection, where they must not only identify fire events rapidly but also transmit large volumes of sensor data securely to ground stations. Achieving both fast on-board analysis and high-speed encrypted data transmission within the size, weight, and power limits of UAV platforms remain a major technical challenge. In this study, we introduce a compact, FPGA-based system that simultaneously performs real-time fire detection and high-throughput data encryption. Our system integrates a programmable logic chip (FPGA), deep-learning models for visual recognition, and AES-256 cryptographic cores onto a single hardware module. A key innovation is a shared scheduling mechanism that coordinates these two functions efficiently. Furthermore, we demonstrate how artificial intelligence contributes beyond image classification: a lightweight neural network monitors input data streams and dynamically adjusts encryption key parameters, thereby improving security without compromising performance. The hardware supports encrypted data transfer rates of 800 megabits per second at a latency of just 2 microseconds, while identifying fire signatures at 30 frames per second. Extensive testing, including cross-validation on a 50,000-frame dataset and environmental stress testing from –20 °C to 55 °C, confirms robust performance under real-world conditions. While the current memory footprint limits multi-camera input, this work offers a foundational design for future systems that aim to combine edge computing, secure communications, and AI-driven perception in autonomous aerial platforms.
Co-Authors Akhmetov, Kairat Atanov, Sabyrzhan Bakyt, Makhabbat Belgibekov, Niyaz Galymzhan, Anuar Kalmanova, Dinara Kuanysh, Absalyam Kyzyrkanov, Abzal Maidanov, Adil Moldamurat, Aibek Nagymzhanova, Karakat Peryakina, Lyudmila Ryspaev, Askhat Sapabekov, Abylaikhan Seitbattalov, Zhexen Seitkulov, Yerzhan Shabayev, Yuriy Spada, Luigi La Tazhikenova, Sapiya Tilenbayev, Alzhan Tulembayeva, Aigul Yergaliyev, Dastan Yergaliyeva, Banu Yessilov, Assylkhan Zeeshan, Nida Zhakupov, Altynbek Zhanibek, Kazybek bi Zhanzhigitov, Syrym Zhumabayeva, Assel Zhumazhanov, Berik Zinagabdenova, Dariga