Advanced Machine Learning Techniques for Enhancing Data Security in Cloud Computing Systems
Dr.Ravinder Mogili
Professor and Head
Dept. of Computer Science and Engineering
Jyothishmathi Institute of Technology and Science
(JNTUH)
Karimnagar,Telangana,India
mogili.ravinder@jits.ac.in
Revelli Varshini
UG Student
Dept. of Computer Science and Technology
Jyothishmathi Institute of Technology and Science
(JNTUH)
Karimnagar,Telangana,India
revellivarshini@gmail.com
Dr.G Srilatha
Associate Professor
Dept. of Computer Science and Engineering
Jyothishmathi Institute of Technology and Science
(JNTUH)
Karimnagar,Telangana,India
gksrilatha8@gmail.com
Pathem Manichandana
UG Student
Dept. of Computer Science and Technology
Jyothishmathi Institute of Technology and Science
(JNTUH)
Karimnagar,Telangana,India
pathemmanichandana@gmail.com
Sujana Patil
UG Student
Dept. of Computer Science and Engineering
Jyothishmathi Institute Of Technology and Science
(JNTUH)
Karimnagar,Telangana,India
sujanapatil04@gmail.com
Kodam Rasagnan
UG Student
Dept. of Computer Science and Technology
Jyothishmathi Institute of Technology and Science
(JNTUH)
Karimnagar,Telangana,India
bunnykodam3@gmail.com
Abstract— Cloud computing is one of the most important technologies in today’s digital ecosystem. Various organizations around the globe use cloud computing services to store their huge amount of data. Even though cloud computing offers many advantages, including flexibility, scalability, and cost-effectiveness, it is one of the most vulnerable technologies in terms of cyber attacks, including data breaches, insider attacks, malware, and denial-of-service attacks.
Traditional techniques, including firewall protection, cannot be considered effective in detecting new types of attacks. To mitigate these types of attacks, this research proposes a machine learning-based cloud computing security framework, including Random Forest, Deep Neural Network, and Reinforcement Learning (Q-learning).
Experimental outcomes revealed that the proposed model, including a Deep Neural Network, achieved a high accuracy of 97%, compared to Random Forest, which achieved an accuracy of 95%, and Reinforcement Learning, which achieved an accuracy of 88%.
Keywords— Cloud Security, Machine Learning, Deep Learning, Reinforcement Learning, Intrusion Detection.
