Introduction to Data Mining
Vandana P. Janeja
Abstract
This chapter gets into the techniques of data analytics, focusing on the three pillars of data mining, namely clustering, classification, and association rule mining, and how each can be used for cybersecurity. This chapter can be seen as a crash course in data mining. It begins with an understanding of the overall knowledge discovery and data mining process models and follows the elements of the data life cycle. This chapter outlines foundational elements such as measures of similarity and measures of evaluation. It outlines the landscape of various algorithms in clustering, classification, and frequent and rare patterns.
Topics & Concepts
Cluster analysisData miningComputer scienceAssociation rule learningData scienceSimilarity (geometry)Process (computing)Knowledge extractionAnalyticsArtificial intelligenceImage (mathematics)Operating systemData Mining Algorithms and ApplicationsNetwork Security and Intrusion Detection