Detecting AI-Generated Phishing Websites with ML

Abstract

In the modern digital landscape, phishing has become among the most pervasive and enduring risks. It is a technique of impersonating a trustworthy entity with the express intent of convincing victims to reveal financial or personal information, including credit card numbers, bank account details, or passwords. The reason phishing is so dangerous is that, rather than exploiting software weaknesses, it often exploits psychological weaknesses, such as urgency, anxiety, or simple curiosity. It is this psychological element that even experienced users may sometimes succumb to. Phishing comes in many forms. The most common type includes emails that pose as reputable companies or banks and ask recipients to "verify" or "update" their accounts. Spear phishing is a highly focused type that targets particular people or organizations after conducting extensive background research, making the effort much more credible. Clone phishing involves hackers replicating authentic emails and substituting harmful attachments or links. These changing tactics demonstrate that phishing is a perennial challenge for cybersecurity experts, as it evolves both technologically and socially. Phishing's overall effects are concerning. According to studies, it plays a significant role in global cybercrime, resulting in billions of dollars in losses each year from illicit transactions or stolen data. Organizations all throughout the world reported losses of more than $billion in 2023 alone due to phishing-related incidents. The issue has expanded beyond what conventional security filters can manage, with attackers now even utilising AI-generated content to produce convincingly phoney websites and emails. Because of this, it is crucial to investigate fresh, innovative solutions that can change as quickly as the threats do.