Mining Cybersecurity Intelligence From Spam Emails Using the AI-Based Generative Adversarial Network
Sriram Kotha, S. Hariharasitaraman, Nilamadhab Mishra, N. D. Patel, Adarsh Patel, Saroja Kumar Rout · Advances in computational intelligence and robotics book series · 2024
The proposed work highlights distinguishing characteristics of document content. A significant amount of effort has been put into the field of spam filtering. GANs are an advanced artificial intelligence system that combines the power of two neural networks: a generator and a discriminator. The generator creates data (emails), while the discriminator evaluates accuracy. Through this adversarial process, GANs learn to distinguish between spam and legitimate emails by detecting minute patterns and irregularities. Phishing emails are generally considered spam emails. Any unsolicited, irrelevant, or unwanted message sent over the internet to promote, phish, disseminate malware, or engage in other nefarious acts is called spam. Phishing emails purposely try to fool people into disclosing private information like passwords, credit card numbers, or personal information by pretending to be from a reliable source. Social engineering tactics are frequently used in these emails to trick recipients into doing things that might compromise their security.