An analytical review of Email Spam Recognition Using Deep Learning
Email spam detection has become a serious issue in contemporary communication systems as a result of the proliferation of unwanted emails. Traditional methods often fall short of the ever- evolving tactics employed by spammers. Deep learning methods provide promising avenues to raise the effectiveness and precision of spam identi- fication systems. This paper looks at the current advancements in the usage of deep learning algo- rithms for email spam identification. We provide experimental data, review relevant literature, dis- cuss techniques, and render conclusions about the efficacy of deep learning in reducing unsolicited emails.
Authors
- Dimple Tiwari (ORCID: https://orcid.org/0000-0001-7556-0078)
- Bhoopesh Singh Bhati (ORCID: https://orcid.org/0000-0001-8476-2798)
- Rajni Devi
- Sonam Juneja
Institutions
- Chandigarh University (IN)
- Guru Gobind Singh Indraprastha University (IN)
- Indian Institute of Information Technology Allahabad (IN)
Publication Details
- Published
- 2024-11-22
- DOI
- https://doi.org/10.1109/aece62803.2024.10911051
- Citations
- 1
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.78