Abstract: To keep an eye out for criminal actions like theft, data modification, and system disruption on one or more computers, we develop an intrusion detection framework. Digital attacks that are dynamic and complex are difficult for traditional intrusion detection systems to detect. But utilizing reliable methods, such various kinds of artificial intelligence, can raise detection rates, lower false alarm rates, and provide affordable solutions. Particularly in data mining, continuous pattern analysis, categorization, aggregation, and real-time data processing are made possible. This research study offers a targeted analysis of the literature on enhanced intrusion detection techniques using data mining and artificial intelligence.[2] In order to provide an analysis, synthesis, and succinct overview of their contents, we identify pertinent publications based on the volume of citations or emerging trends. We also emphasize data's crucial significance in data mining and artificial intelligence.[4]
Keywords: Intrusion detection framework, Artificial Intelligence, data mining, cyber security, cyber resilience
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DOI:
10.17148/IJARCCE.2024.13461
