Phishing Attack Analysis: Estimating Key Cluster Features and Why It’s Important

4 First, let’s quickly review the clusters we built to understand phishing attacks. Using data we collected over the course of a year spent tracking and taking down phishing cases for a major U.S. financial institution, we extracted features from four categories: similarity analysis, structure analysis, phishing visitors tracking and domain registration. Then, using the expectation-maximization clustering algorithm, we examined three groups of attacks as shown in the following figure.. [Read More]

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