A Survey: Network Attack Detection and Mitigation Techniques

Network attack detection and mitigation systems (NADMS) is developed as defending software to detect malicious cyber-attacks, safeguard critical infrastructure, and protect sensitive data. NADMSs are recently been researched for enhanced version of security systems based on machine learning (ML), Blockchain, and diverse network frameworks. There are numerous network attacks. As technology enhances, even cyber-treat also increases. Hence, networks need to be secured from these increasing and diverse network attacks. The aim of the presented research survey is to study various optimization techniques used to detect and mitigate different types of attacks. The research gaps are identified and future activities, emphasizing the critical need for adaptive, scalable NADMS frameworks in the dynamic cyber-threat context are suggested. The study also discussed the significance of distributed denial-of-service (DDoS) attacks, providing information on efficient detection and mitigation techniques. The survey focused real-world situations and current network security issues. The consolidated comparison represented as a result of survey can be referred to identify and select appropriate detection and mitigation tools and techniques based on the type of network attacks.