Boruta Feature Selection Applied to Classification Algorithms for Intrusion Detection

Today, cloud computing is a sure bet for companies that need to find modern, adaptable IT solutions to handle colossal amounts of business data, and can help companies improve efficiency and productivity, but on the other hand cloud computing is a constantly evolving technology, and attackers are constantly looking for new ways to compromise the security of data hosted in the cloud, for example, attackers can steal data hosted in the cloud by downloading or encrypting it, or even attackers can launch DDoS attacks against cloud infrastructures to make them inaccessible. In order to solve this type of problem, we propose the solution presented in this paper, intrusion detection in a cloud environment using a multiple classification algorithms, but to get more accurate results, we apply the step of selecting the relevant attributes of our dataset using the Boruta algorithm.