Efficient Identification of DDoS Attacks on Cloud Computing Environment using Machine Learning Techniques
International Journal of Engineering Research in Computer Science and Engineering · 2022
The internet gives us beneficial data and information for personal, social, and economic growth. The security issue will be the main challenge on the internet. As the cloud technology is more popular, the first advantage of a cloud is flexibly scales to satisfy a variable demand, blew up instantly, blew down when demand moderates– in subsequent. So it requires expanse shielding from a DDoS attacks to challenge interlude effects of a DDoS Attacks. DDoS attacks are the malicious endeavor to interrupt normal traffic in a web property i.e., critical attacks that negotiates the accessibility of the network. On the cloud environment, aiming at efficiently analyzing and detecting the DDoS attacks, we propose four machine learning techniques i.e., the Naive Bayes, Support Vector Machine, K-nearest neighbor, and Random Forest.