Intrusion Detection System Using the G-ABC with Deep Neural Network in Cloud Environment

Cloud computing plays a pivotal role in sharing resources and information. It is challenging to secure cloud services from different intruders. Intrusion detection system (IDS) vital detecting intruder attacks, it also used monitor the traffic network. The paper aimed control attacks using machine learning (ML) technique integrated with artificial bee colony (ABC) named Group-ABC (G-ABC). IDS detector has been implemented further simulation results have determined G-ABC. evaluation carried out measures such as precision, recall, accuracy, F-measure. Different user root (U2R), probe, local (R2L), backdoors, worms, denial-of-service (DoS) detected. analysis performed two datasets, namely, NSL-KDD dataset UNSW-NB15 dataset, comparative against existing work prove effectiveness of proposed IDS. objective determine attacker deep technique.