E-mail Sink AI: Deep Learning model for multiclass E-mail Classification for Forensic Analysis using Design Thinking.

Abstract

E-mail is an essential application for carrying out transactions and efficiency in business processes to improve productivity. E-mail is frequently used as a vital medium of communication and is also being used by cybercriminals to commit crimes. Cybercrimes like hacking, spoofing, phishing, E-mail bombing, whaling, and spamming are being performed through E-mails. Hence, there is a need for proactive data analysis to prevent cyber-attacks and crimes. Keeping in sight these limitations, this project proposed to design a novel efficient approach named E-mailSinkAI for E-mail classification into four different classes: Normal, Fraudulent, Threatening, and Suspicious E-mails by using LSTM based GRU. The LSTM based GRU efficiently captures meaningful information from E-mails that can be used for forensic analysis as evidence. E-mailSinkAI effectively outperforms existing methods while keeping the classification process robust and reliable.