Optimization of Data Obfuscation in Big Data Processing and Storage Systems

This paper studies the problem of reducing the attack surface from an internal attacker in heterogeneous systems for processing and storing big data by selecting the optimal data obfuscation method based on anonymization technologies. The study analyzes the terminology and systematizes data-hiding methods to reduce the attack surface in big data processing and storage systems. A formal formulation of the problem of finding the optimal data obfuscation method and an algorithm for solving it across various types of datasets are proposed, taking into account evaluation criteria specific to each class of methods. The implementation of a software prototype for supporting decision-making and selecting the optimal method for solving practical problems is described. Experimental testing and analysis of its results are carried out.