As we know that security is a concerning topic for each country. There are numerous intrusions launched by numerous attackers, and each attacker attempts to breach the security system in order to gain advantages in various scenarios. We can use a behavioral approach to capture the attack and classifying the type of attack becomes more important in this situation. There are so many choices of algorithms that are available, the researchers select appropriate tools to classify the type of data. IDS (Intrusion detection system) is a software application that monitors malicious activities and produces reports. There are so many types of IDS systems available nowadays; some intrusion detection systems are network-based, signature-based, or anomaly-based. Many researchers work with anomalous data to classify attacks. We are using an SVM (Support Vector Machine) classifier for this purpose. The main thing in SVM is the selection of kernel, which has the primary role of classifying data classes. For this purpose, we used the RBF function as a kernel for better results.