Email Spam Detection Using LSTM with Attention Mechanism

Spam email detection is an important domain of cybersecurity because spam emails usually contain phishing URLs, malicious attachments, or fraudulent advertising content. These emails not only interfere with communication but also lead to major threats like data robbery, money loss, and system compromise. The conventional rule-based spam filters have been ineffective in dealing with these issues as they lack high adaptability in handling changing spam tactics. In this research, we propose a deep learning-based solution for spam filtering with an LSTM network with an attention mechanism. The model is formulated to efficiently capture sequential and contextual information from email content through highlighting