Machine Learning Algorithms for Cloud Security

Abstract

Any cloud data storage model's main goal is to make data accessible without sacrificing its security. Any model of cloud data storage that aims to ensure safety and effectiveness must take security into account. This research offers a secure model for cloud-based data protection. The suggested model offers a solution to the security problems that the cloud faces, including protection of data from infringements and defense against users with fictitious authorizations which have a negative impact on cloud security. The advantages and efficiency of security in cloud computing are provided by our suggested paradigm, which also improves cloud data encryption. It offers users of cloud computing security and scalability of data exchange. Our architecture satisfies the security requirements for cloud computing, including encryption, authorization, identification and authentication. Additionally, this architecture guards the system against any fictitious data owner who enters dangerous data that could undermine the primary objective of cloud services.