Ensuring Data Confidentiality During Data Analysis in Information Systems

This paper examines scientific methods for guaranteeing data privacy during analysis in information systems. It explores data protection challenges in the digital age, where information is crucial for all sectors. While data growth and analysis advancements allow studying society and business, storage, processing, and analysis pose privacy threats like unauthorized access and leaks. The paper highlights various scientific methods for data privacy in information systems, focusing on combining data anonymization (removing personal details) with l-differential privacy (adding noise) to ensure high privacy while enabling valuable data analysis.