Advanced Analysis of Learning-Based Spam Email Filtering Methods Based on Feature Distribution Differences of Dataset

Advanced Analysis of Learning-Based Spam Email Filtering Methods Based on Feature Distribution Differences of Dataset

Spam emails, which are unsolicited bulk emails, pose a significant threat in digital communication security. To counter spam emails, learning-based spam email filtering methods have been extensively studied. However, as spam patterns evolve, these methods face challenges in maintaining the accuracy...

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Bibliographic Details
Main Authors: Jin-Seong Kim, Han-Jin Lee, Han-Ju Lee, Seok-Hwan Choi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Spam email filtering
recurrent neural network (RNN)
gated recurrent unit (GRU)
long short-term memory (LSTM)
ALBERT
security
Online Access:https://ieeexplore.ieee.org/document/10750179/
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