Enhancing the Performance of an Intrusion Detection System Using Novel Deep Reinforcement Learning Algorithms

Abstract

With the rapid development of cyber security, the need for intrusion newlinedetection has become paramount to secure the digital systems and networks from newlinemalicious activities. Intrusion detection is the way of analyzing and monitoring newlinesystem or network activities to detect and respond to abnormal behavior, newlineunauthorized access, or security breaches. Intrusion Detection Systems (IDSs) has newlinebeen instrumental in proactively detecting vulnerabilities, potential threats, and newlinemalicious activities that may compromise the integrity, confidentiality, or availability newlineof highly sensitive information. Such systems monitor user behavior, network newlinetraffic, and system logs to identify patterns indicative of unauthorized access, newlinemalware infections, or other security incidents. The prompt identification of these newlineanomalies allows for quick response and mitigation measures, which prevents newlineunauthorized access and potential damage. newline Intrusion detection and classification using Artificial Intelligence (AI) newlineincludes the advancement of intelligent algorithms capable of identifying anomalies newlineand categorizing them based on the context and severity newline