Building AI Applications Using Deep Learning

Recently, we have seen a huge boom around the field of deep learning; it is currently being implemented in a wide variety of fields, from driverless cars to product recommendation. In their most primitive form, deep learning algorithms originated in the 1960s. If the concept has been around for decades, why is it that widespread... Continue Reading →

Machine Learning Explained

Machine learning models are often dismissed on the grounds of lack of interpretability. There is a popular story about modern algorithms that goes as follows: Simple linear statistical models such as logistic regression yield to interpretable models. On the other hand, advanced models such as random forest or deep neural networks are black boxes, meaning... Continue Reading →

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

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... Continue Reading →

Fraud Detection That Accounts for Misclassification Using Cost-Sensitive Logistic Regression

Fraud detection is a cost-sensitive problem, in the sense that falsely flagging a transaction as fraudulent carriesa significantly different financial cost than missing an actual fraudulent transaction. In order to take these costs into account, companies should use a more business-oriented measure such as “Cost,” which allows companies to make decisions that are better aligned... Continue Reading →

Clustering of Phishing Attacks

In a recent report we showed how we are able to gain better understanding of phishing attacks and attackers by using cluster analysis. This post lays out in greater detail how to create those clusters by examining the features and methods used.For the study, we used the data collected over the course of more than a year... Continue Reading →

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