A Survey on Cloud Attack Detection using Machine Learning Techniques
Gavini Sreelatha, A. Vinaya Babu, Divya Midhunchakkarvarthy · International Journal of Computer Applications · 2020
Cloud concepts such as resource sharing, outsourcing, and multi-tenancy create significant challenges to the security community.Also, trusted third party and web technologies based cloud service provisioning arises new security threats in the cloud environment.Cloud security has become a vital research area with new security models, protocols, and policies in recent years.Despite the fact, the existing cloud security research still faces the shortcomings in improving the detection accuracy and detecting the new or unknown attacks in the cloud.To address the constraints above, many security researchers have focused on developing cloud security models with the assistance of the machine learning methods.Machine learning techniques play a significant role in automatically discovering the potential difference between legitimate and malicious data with high accuracy.The deep learning is a branch of machine learning that provides remarkable performance in cloud security issues.This survey provides a comprehensive study of cloud security concerns, traditional security measures, and machine learning-based security solutions in the cloud environment.Initially, it identifies cloud vulnerabilities and presents state-of-the-art methods to control security threats, weaknesses, and attacks.This work also reviews the security solutions developed by machine learning and deep learning techniques for the cloud environment.