Legal Protection of Personal Data in Big Data Analysis: Threats and General Rules

Abstract

This article provides a comprehensive analysis of the pressing issues related to personal data protection in the context of Big Data. The distinctive features of four types of data within the Big Data framework provided, observed, derived, and inferred dataalong with their protection mechanisms and security requirements are examined in detail. The principles of data protection, particularly the principles of fairness and transparency, and the necessity of implementing them in national legislation are substantiated from both theoretical and practical perspectives. The concept of threats to the security of data within the Big Data framework is developed, along with recommendations for what it should entail. The discriminatory characteristics of automated decision-making and profiling processes, as well as their impact on individual rights, are deeply analyzed. The complexity of Big Data analysis, which can lead to opacity in processing for citizens and consumers whose data is used, is highlighted. The necessity of developing new legal mechanisms to protect the rights of data subjects and ensure data confidentiality and security is substantiated.