Protecting and Mitigating Against Cyber Threats

7Email Spam Classification Using Novel Fusion of Machine Learning and Feed Forward Neural Network Approaches

Keshetti Sreekala^1*, Maganti Venkatesh², M. V. Ramana Murthy³, S. Venkata Meena⁴, Srinivas Rathula⁵ and A. Lakshmanarao⁶

¹Department of CSE, Mahatma Gandhi Institute of Technology (A), Hyderabad, India

²Department of AI&ML, Aditya Engineering College, Surampalem, A.P., India

³Department of CSE, Raghu Engineering College, Visakhapatnam, India

⁴Department of CSE, Avanthi Institute of Engineering and Technology, Cherukupally, A.P., India

⁵Department of IT, B V Raju Institute of Technology (A), Narsapur, A.P., India

⁶Department of IT, Aditya Engineering College, Surampalem, A.P., India

Abstract

In the age of information, electronic conversation has become an integral unit of our daily lives. However, this satisfaction is accompanied by the continual challenge of email spam, which not only inundates inboxes but also presents a severe peril to cybersecurity. Email spam rests a pervasive issue, with usual spam filters regularly struggling to adapt to evolve spamming techniques. This paper intends to present progressive advanced ML and DL techniques. This paper introduces an innovative solution that leverages a strategic ensemble of the two Machine Learning (ML) and Feed Forward Neural Network (FNN) to improve the accuracy and efficiency of email spam categorization. By employing cutting-edge algorithms and models, the goal is to build a robust and resilient system capable ...