Comparative analysis of security models in cloud platforms

• Published in: Известия Томского политехнического университета: Промышленная кибернетика Vol. 2; no. 2; pp. 1 - 16
• Main Author: Semen M. Levin
• Format: Journal Article
• Language: English
• Published: Tomsk Polytechnic University 25.06.2024
• Subjects: access management; adaptive security systems; artificial intelligence in security; blockchain in data protection; cloud technologies; compliance with regulatory requirements; cyber threats; data encryption; data security; security monitoring
• ISSN: 2949-5407
• DOI: 10.18799/29495407/2024/2/50

This article is dedicated to the importance of data security on cloud platforms, highlighting the subject relevance in an era where threats to information security are becoming increasingly complex and sophisticated. The primary focus is a comparative analysis of security models employed by leading cloud platforms such as Amazon Web Services, Microsoft Azure, Google Cloud Platform, IBM Cloud, and Oracle Cloud. The research covers various crucial security aspects, including data encryption, identity and access management, monitoring mechanisms and incident response. The article sheds light on current trends and technologies in cloud data protection, including the use of artificial intelligence and machine learning to enhance threat detection efficiency and the implementation of confidential computing and blockchain technologies to improve data protection. Issues of compliance with legal requirements and data security standards are discussed, along with recommendations for organisations to optimise information protection in the cloud environment.