Fraudulent emails are deceptive measures that are taken up by goons for personal gain in order to lure in innocent people. They are used to scam and defraud people. The emails usually involve offers that are too good to be true, and they are targeted towards naive individuals.
In this chapter, we will describe how spam emails work, and we will list a few machine learning algorithms that can mitigate the problem. The chapter will be divided into the following sub-sections:
- Fraudulent emails and spoofs
- Types of email fraud
- Spam detection using the Naive Bayes algorithm
- Featurization techniques that convert text-based emails into numeric values
- Spam detection with logistic regression
