Browsing by Author "Laktionov, I. S."

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Intelligent Sentinel Satellite Image Processing Technology for Land Cover Mapping
(Dnipro University of Technology, Dnipro, 2024) Kashtan, Vita Yu.; Hnatushenko, Volodymyr V.; Laktionov, I. S.; Diachenko, H. H.
ENG: Purpose. This article proposes to develop an intelligent Sentinel satellite image processing technology for land cover mapping using convolutional neural networks. The result will be an image with improved spatial resolution. Methodology. The paper presents a technology using a combination of biquadratic interpolation, histogram alignment, PCA transform, as well as a parallel residual architecture of convolutional neural networks. The technology increases the information content of Sentinel-2 optical images by combining 10 and 20-meter resolution data, resulting in primary 20-meter images with improved spatial resolution. Findings. The root mean square error (RMSE = 3.64) indicates a high accuracy in reproducing the spectral properties of the images. The correlation coefficient (CC = 0.997) confirms a high linear relationship between the estimated and observed images. The low value of Spectral Angle Mapper (SAM = 0.52) with the high Universal Image Quality Index (UIQI = 0.999) indicates high quality and structural similarity between the synthesized and reference images. These results confirm the proposed technology’s effectiveness in enhancing the spatial resolution of Sentinel satellite images. Originality. Traditional pansharpening methods of multispectral images developed for satellite images with panchromatic channels cannot be directly applied to Sentinel multispectral data, because these images do not contain a panchromatic channel. In addition, atmospheric conditions and the presence of clouds affect the quality of optical images, complicating their further thematic processing. The proposed technology, using biquadratic interpolation, histogram alignment, convolutional neural networks, and PCA transformation, removes clouds and enhances the spatial resolution of the primary 20-meter optical satellite image channels of Sentinel-2. This technology reduces color distortion and increases the detail of digital optical images, which allows for more accurate analysis of the state of the earth’s surface. Practical value. The results obtained can be used to improve the methods for processing Sentinel satellite images, which provide high spatial resolution and accurate preservation of spectral characteristics. It provides the foundation for the development of new geographic information systems for land cover monitoring.
Simulation-Driven Assessment of Cryptographic Algorithms for Resource-Constrained Infocommunication Networks
(Dnipro University of Technology, Dnipro, 2025) Laktionov, I. S.; Hnatushenko, Volodymyr V.; Udovyk, Iryna M.; Olevskyi, V. I.
ENG: Purpose. To conduct a multi-criteria evaluation and analysis of the performance of encryption algorithms that may be potentially resistant to contemporary cyberattacks, including quantum attacks. The evaluation takes into account the ability of the algorithms to be deployed on devices with limited computational resources within the infocommunication networks during the transmission of information messages. Methodology. Software implementation, testing and validation of selected cryptographic algorithms based on Python, considering the impact of limited resources and destabilising factors, such as signal noise components, based on computer experiments were applied. The performance of the studied cryptographic algorithms was analysed using statistical data processing methods and a multi-criteria evaluation approach. Findings. The symmetric algorithms AES-256-GCM and ChaCha20-Poly1305 demonstrated the highest accuracy in signal recovery following encryption and decryption (MSE ranges from 1.95 · 10-6 to 5.12 · 10-5). The time taken to encrypt and decrypt I/Q signals using symmetric algorithms was found to be around 2.5 times faster than that required by the Kyber family. Computer experiments confirmed the existence of a trade-off between processing speed and security level. Symmetric algorithms are optimal for scenarios with critical processing speed requirements. However, Kyber provides greater protection reliability, albeit at the cost of additional resources. The correctness of the proposed computer model, which enables the computational and information-functional characteristics of cryptographic algorithms to be evaluated, has been proven. Originality. Patterns of the destabilising influence of signal-to-noise ratio indicators and signal length on the accuracy of digital signal recovery after encryption have been established for different cryptographic algorithms (AES, ChaCha20 and the Kyber) in the context of their use in resource-constrained infocommunication systems. Practical value. Implementing the computer model proved its suitability for studying cryptographic algorithms in resource-constrained environments, as well as its potential for improving information security protocols and selecting optimal algorithms based on processing speed requirements and desired security levels.