Intrusion Detection in Networks using Gradient Boosting

Technology now a days has become the most important requirement in daily .As the use of technology increases the threats also enhanced as most of the applications always require internet to access data through network. Due to threats the attacks can be easily done on the systems to grab sensitive information. To reduce these attacks and have less amount of damage intrusion detection systems were developed .These systems identify abnormal activity and raises alerts .Based on these alerts intrusion prevention can be carried out. On the basis of the dataset that is supplied, we apply machine learning approaches in order to detect and categorise the intrusions. The dataset that is used is CICIDS 2017.In this we have discussed a machine learning algorithm XBoost(Extreme Gradient Boosting)classifier to classify different attacks that happen on the network. This algorithm has provided an accuracy of 93%.