IJAIEM

Veuturi Venkata Chamikar, Matam Pooja, Muppala Maruthi , G Gouthami

Abstract

As cloud computing becomes more important for storing and managing data, keeping this information safe is crucial. This paper looks at how advanced machine learning techniques can improve data security in cloud systems. We tested three different models: a Random Forest model, a Deep Neural Network (DNN), and a Q-learning Model. The Random Forest model achieved 95% accuracy in detecting security threats, effectively distinguishing between real threats and safe activities. The DNN performed even better, with 97% accuracy and an excellent ability to identify threats. The Q-learning model detected 88% of threats but needs improvements to reduce incorrect Alerts. Overall, our findings show that machine learning can significantly enhance the security of cloud data. These insights can help organizations develop strong security measures that adapt to new cyber threats, ultimately protecting their cloud-based information better.