Data Mining Techniques Against Cyber Threats: A Review

Abstract

Abstract Data mining is a technique used to extract useful data from existing databases. Those datasets are now being shared globally. Secure communication and confidentiality are required because data from multiple sources must be collected and stored in one central location. Data mining technology involves methods that rapidly and efficiently convert vast quantities of data into relevant insights adapted to the user's requirements. Unfortunately, the utilization of data mining expertise to acquire sensitive personal information poses a threat to individuals' privacy rights.

 This paper provides a review of the current techniques for preventing cyber risks and safeguarding privacy through the application of data mining. Data mining is used to examine, analyze, and figure out the structure and behavior of data mining organizations. Implementing data mining with optimal outcomes is a challenging task. In the past decade, academics have extensively studied many elements of data extraction. Therefore, it is crucial to provide published research evidence pertaining to this field. For this study, a thorough evaluation was carried out of more than thirty research papers sourced from reputable literature databases.

The objective was to extract significant information regarding the field of data mining. The collected data was then used to address various study inquiries about cutting-edge extraction methodologies, data mining mechanisms in cyber dangers, data extraction procedures, algorithms, and evaluation techniques. This paper discusses various research areas and issues in data mining, serving as a valuable reference for researchers in this domain.