Classification of Bruteforce Attacks Using Convolution Neural Network

The computer technology is being advanced day by day such that it results in being subjected to various data breaches and network attacks that might cause a huge damage to the data and the network. These network attacks cannot be ignored and must be prevented to maintain the at most security so that the integrity is maintained. Thus, the crucial job for the network administrators in the current generation is to choose better preventive measures so that the network is not vulnerable to the hackers. The Intrusion Detection Systems are one of the best solutions to prevent the further damage that can be caused by the hackers. We propose to develop a deep learning model using convolution neural network (CNN) to analyze the network traffic and classify the type of Bruteforce attack that has been performed. This method will be validated using a portion of CICIDS-2019 dataset. The model is proposed such that it is efficient enough to classify the network attack and have an improved accuracy when compared to other machine learning models.