Clustering for security challenges

Abstract

Data science, which includes statistics, probability, data mining, machine learning and natural language processing, is on a major uptrend. Clustering is a key data science method, which does not require labeled data. This tutorial will cover clustering for security challenges. We expect to cover both classical clustering techniques and some of the important, newer clustering algorithms. Examples will be drawn from clustering of malware datasets and phishing emails. Throughout the discussion, we will highlight some of the key unique needs of the security domain that are relevant for clustering techniques.