Cyber Security against DDoS, Malware, Spoofing Attacks using Machine Learning with Genetic Algorithm

Abstract

 The cyber security is a practice measure to prevent the data online. Worldwide lock down period amid COVID19 crisis resulting high gain in online users and data processing along with transactions, confidential information is required to be prevented from any kind of misuse. Implementing effective cyber security measures has become difficult task as today there are more devices than people. This paper presents a new approach using extended Genetic Algorithm for the selection of attributes followed by neural training and classification for three different cyber threats namely Distributed Denial of Service (DDoS), malware and spoofing. Precision, recall and F-measure is calculated and is also compared with recent research articles cited in the reference list.