Port-Scanning Attack Detection Using Supervised Machine Learning Classifiers

Different attacks are done on data confidentiality, integrity, and availability. A famous type of network attacks is Port Scanning. Port Scanning attacks are done by attackers to know gather information about the devices and to know what services are running on. This study focuses on detecting port scanning attacks by using different machine learning algorithms and comparing between them to find the best one. Some algorithms reach near 100 percent of accuracy with detecting this type of attacks like Decision Tree and Random Forest with short time of training and testing.