Unsolicited emails, often known as spam, pose a persistent and serious
problem in today’s digital world and have become a big concern for every email user
over the past few years. Users find it annoying, but individuals who fall victim to
frauds and other attacks also suffer harm as a result. Spam emails are now
manufactured, created, or written in such a unique way that anti-spam algorithms find it
hard to recognise them. Email spamming strategies are becoming increasingly
complex, shifting away from traditional and direct spamming approaches toward a
more scalable, covert, and indirect method of using botnets to disseminate email spam.
This chapter examines the persistent problem of spam email, its adverse effects, and
practical methods for identifying and reducing it. It examines the origins and evolution
of spam email, highlighting its detrimental effects on individuals, organizations, and
society. It examines various detection techniques, including rule-based methods and
machine learning algorithms. The chapter also examines mitigation techniques and
countermeasures, including spam filters and blacklisting.
Keywords: Algorithms, Blacklists, Businesses, Communication, Data, Detection, Effective, Email addresses, Legitimate emails, Machine learning, Phishing, Scam, Solicited emails, Spam emails, Spam filters, Techniques, Undesirable, Unsolicited emails, User, Whitelists.
