Enhancing Cybersecurity: Smart Intrusion Detection in File Server SYSTEMS

Abstract

System security is a major challenge worldwide, which has led to the increasing implementation of security surveillance systems in the public and private sectors. Likewise, it is inevitable to secure server-based systems that store vast amounts of sensitive data that is accessed from time to time. Intrusion Detection Systems (IDS) use metrics to detect anomalous activity on computers and computer networks. Modern detection algorithms try to reach detection metrics by acting as an antivirus. This is not enough, the need to explore more controlled, porous, and more secure systems is inevitable, hence this research. Therefore, this study’s main objective is to develop smart intrusion detection systems for file servers and client machines that can be used within any networked environment. A qualitative research methodology was employed in the study. The sources of information included four databases: SpringerOpen, EBSCO, Google Scholar, and Direct Science. The key findings of the study are that cyber-attacks and threats are increasing, and new strategies are needed to handle them because the current intrusion detection systems experience challenges and are unable to detect malware. Intrusion detection systems are the next-generation protection, which offers the visibility to identify advanced threats within legitimate content, even authorized applications and trusted sources. Organizations are recommended to implement smart IDSs in front of file server systems and behind the firewall to ensure all malware is filtered.