Chaos-based image encryption schemes are applied widely for their cryptographic properties. However, chaos and cryptographic relations remain a challenge. The chaotic systems are defined on the set of real numbers and then normalized to a small group of integers in the range 0–255, which affects the security of such cryptosystems. This paper proposes an image encryption system developed using deep learning to realize the secure and efficient transmission of medical images over an insecure network. The non-linearity introduced with deep learning makes the encryption system secure against plaintext attacks. Another limiting factor for applying deep learning in this area is the quality of the recovered image. The application of an appropriate loss function further improves the quality of the recovered image. The loss function employs the structure similarity index metric (SSIM) to train the encryption/decryption network to achieve the desired output. This loss function helped to generate cipher images similar to the target cipher images and recovered images similar to the originals concerning structure, luminance and contrast. The images recovered through the proposed decryption scheme were high-quality, which was further justified by their PSNR values. Security analysis and its results explain that the proposed model provides security against statistical and differential attacks. Comparative analysis justified the robustness of the proposed encryption system.

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The paper proposes an automated method of classification of source code changes, which consists of two steps – clustering and comparison of clusters of classes. The currently existing methods of improving component software development are analyzed. Based on the analysis, it was established that the optimal method of increasing the productivity of the analysis of changes is the clustering of these changes. A method is proposed, according to which the distribution of changes by clusters is carried out automatically. Their comparison to classes is carried out by an expert. It is shown that the automation of the distribution of changes by clusters significantly reduces the time of examination of code changes, which makes it possible to use the obtained results to improve the quality of software during the development of complex software complexes. The results obtained in the course of the work provide an idea of possible data clustering algorithms with further analysis of the obtained set of clusters according to their parameters. Also, on the basis of the conducted research, the results of the comparison of the classifications of changes in the software system with open source code, performed using the proposed automated method and manually, are given. It is shown that the task of controlling changes that are undesirable at the current stage of development is solved significantly more effectively using the proposed method compared to a full examination of changes, as it allows identifying changes of classes prohibited at the current stage of development with less time spent. The application of the method in practice allows to improve the quality of the code due to the increase in the efficiency of the process of its examination. Using the approach proposed in the paper, the examination process under time constraints can be built more efficiently by selecting changes of the most important classes of changes. It has been proven that the method works perfectly if the same type of changes are analyzed, and when the changes combine heterogeneous code modifications, the quality of the automated classification deteriorates. The obtained results make it possible to extend the application of this method to other software complexes and systems, provided that differences in data types and their parameters are taken into account.

The article examines the trends that have led to a significant increase in the legal personality of political parties in many European countries over the last decade. The growing role of political parties in the modern conditions of a developed democracy requires a revision of the standards of European legislation on their activities. Important issues of legal rights and obligations of political parties in accordance with both international standards and the legislation of Ukraine are revealed; defines the concepts of "subject of legal relations" and "legal capacity", as well as the legal side of the legal personality of a political party; formulates precise legal criteria and bases for recognition of a political party as a subject of law. A comparative legal study of the legal personality of political parties in Ukraine and the Member States of the European Union. The European standards on the legal personality of political parties have already been developed in most European countries and are aimed at achieving the constitutional and legal order is noted. The Law on Political Parties is a common denominator of legislative work, which regulates the organization of political parties and the financing of their participation in election campaigns. The development and implementation of standards for regulating the activities of political parties is a very important component of protecting the principles of a democratic society is determined. The importance of the role that political parties play in governance at both the national and supranational levels, this issue is currently given great importance in the European Union are given. The introduction of European standards in national legislation enables the state to effectively regulate the activities of political parties.

Бойчук А. Ю.* к. ю. н., доцент кафедри державознавства і права Одеського регіонального інституту державного управління Національної академії державного управління при Президентові України, суддя Приморського районного суду міста Одеси (м. Одеса, Україна