A Survey on Cyber Security IDS using ML Methods

The growing rate of cyber-attacks on system networks in recent years exacerbates the privacy and security of computer infrastructure and personal computers. Intrusion Detection and Prevention systems are turning into a significant section of computer networks and cyber security. Various techniques are proposed by individuals to mitigate this problem. This gives rise to another problem of which technique should be used for a given scenario. This survey paper provides a solution to the aforementioned problem and presents a comparative study of different proposed models for intrusion detection and prevention systems which consist of machine learning algorithms to attain better performance and accuracy and to enhance cyber security. This paper aims to discern pros and cons of various intrusion detection and prevention techniques to gain better understanding and help researchers make more informed choices in selecting the appropriate security model to produce successful results.