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The intrusions are increasing daily, so there is a huge amount of privacy violations, financial loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such as menacing networks, computer resources and network information. Each type of intrusion focuses on specified tasks, whereas the hackers may focus on stealing confidential data, industrial secrets and personal information, which is then leaked to others for illegal gains. Due to the false detection of attacks in the security and changing environmental fields, limitations like data lagging on actual attacks and sustaining financial harms occur. To resolve this, automatic abnormality detection systems are required to secure the required computing ability and to analyze the attacks. Hence, an efficient automated intrusion detection system using machine learning methodology is proposed in this research paper. Initially, the data are …