Spam Filter Using Artificial Intelligence: PyTorch Framework Based Approach
This paper outlines the development of an artificial intelligence spam detection solution using PyTorch framework. The neural network itself is based on a feed forward neural network where the model will be trained on different datasets to show the overall results of the spam detection. Also the model architecture, used parameters and the training process will be shown from zero to finish and what algorithms used too. At the end of the paper, it will show the developed model efficiently identified and detected messages that exhibited suspicious characteristics.
Authors
- Valéria Póser
- Szandra Anna Laczi (ORCID: https://orcid.org/0009-0000-3104-0708)
- Balázs Tóth (ORCID: https://orcid.org/0009-0002-1092-8796)
Institutions
- Obuda University (HU)
- Buda Health Center (HU)
Publication Details
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1109/sisy62279.2024.10737559
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00