APPLICATION OF EFFECTIVE APPROACHES TO DIGITAL DATA ANALYSIS

Digital data plays a crucial role in modern society, and its analysis is essential for recovering information and understanding events recorded in digital environments. This study focuses on developing and applying methods for analyzing digital artifacts, including deleted files, system logs, browser history, and document metadata. These artifacts enable the reconstruction of user activities, identification of potential vulnerabilities, and risk assessment. The methodology involves creating and analyzing disk images, recovering data, structured interpretation, and reliability evaluation. The results successfully demonstrate the effectiveness of the proposed approaches in identifying key artifacts. Special attention is given to the prospects of using intelligent algorithms, such as machine learning, to automate analysis and improve its accuracy. The methods and findings presented in this study hold significant practical value and can be applied to a wide range of tasks related to processing and studying digital information, as well as serving as a foundation for future research in this field.