Anti-phishing Email Detection Framework for New-Age Phishing Attacks

Email as a form of communication has always been the major target as the co-operate world, including the rest of the internet users, tend to use emails as a form of communication. The rise of COVID-19 has prompted the use of emails much more as employees are working from home, meaning that the day-to-day work is now confirmed and communicated via email. This has prompted the rise of phishing attacks as cybercriminals are aware that users are frequently using emails as a mode of communication now more than ever before. The protection of crucial data has always been the main aim of cybersecurity; however, cybercriminals continue finding new ways and techniques to steal data, as data is always the main target, and the confidentiality of data is always breached, meaning users tend to reveal different types of crucial information without intending to do so. Phishing email remains one of the most common forms of attack which prevails regardless of the different types of techniques used. This paper focuses on the different anti-phishing methods which have been introduced. An exploration of the traditional existing solutions will be reviewed, including the limitations it has when it comes to combating new-age phishing attacks. Existing machine learning techniques will further be analyzed and reviewed, compared in terms of their effectiveness. A review on the use of deep learning techniques that have been used, including blacklisting methods as well. Several awareness techniques to prevent users from falling victim to phishing attacks will further be explored. Observations and analyses made from previous research work will, however, show that there is still a need for anti-phishing improvement.