data security

In today’s world, where technology is developing at an incredible speed, automated information collection systems have become an integral part of our lives. They affect various aspects of society, including subjective human rights. This impact can be viewed from several perspectives. First of all, it is the significant advantages of automated systems. Such information collection systems significantly increase efficiency and accuracy in many areas. They allow for the rapid processing of large amounts of data, which facilitates informed decision-making.

The paper examines the explores the use of artificial intelligence (AI) methods and tools for the efficient construction, management, and optimization of cloud IT infrastructures. The main challenges related to the automation of deployment, scaling, monitoring, and resource optimization in the cloud environment are analyzed, along with the role of AI in addressing these issues. Approaches to integrating AI to improve productivity, reduce operational costs, and enhance the security of cloud platforms are discussed.

ctive methods to protect personal data in online texts. Existing anonymization methods often prove ineffective against complex LLM analysis algorithms, especially when processing sensitive information such as medical data. This research proposes an innovative approach to anonymization that combines k-anonymity and adversarial methods. Our approach aims to improve the efficiency and speed of anonymization while maintaining a high level of data protection.

This article delves into the pivotal role that business analytics plays in the era of Big Data, focusing on how it transforms decision-making processes in contemporary organizations. Big Data analytics has become an essential tool for businesses striving to gain a competitive edge in an increasingly data-driven world. The research outlines the main trends in the application of Big Data technologies, such as the integration of artificial intelligence (AI) and machine learning (ML), predictive analytics, and real-time data processing.

This article explores the creation of a data classification policy in line with SOC 2 Type 2 compliance requirements. SOC 2 Type 2 is a notable certification that attests to an organization’s ability to adhere to the Trust Services Criteria, including security, availability, processing integrity, confidentiality, and privacy.