Spam Detection using Word Embedding-based LSTM

Spam email is a well-known problem in network communications. A large number of spam emails in mailbox caused inconvenience and might lead to cybercrime. Effective spam mail detection is one of challenges research topics. This paper proposed a new spam mail detection approach that can be applied for...

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Bibliographic Details
Main Authors: Thanarattananakin, Supphawarich, Bulao, Suwanna, Visitsilp, Busarin, Maliyaem, Maleerat
Format: Conference Proceeding
Language:English
Subjects:
Computer crime
LSTM
Postal services
Sentiment analysis
Spam Detection
Unsolicited e-mail
Word Embedding
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Summary:Spam email is a well-known problem in network communications. A large number of spam emails in mailbox caused inconvenience and might lead to cybercrime. Effective spam mail detection is one of challenges research topics. This paper proposed a new spam mail detection approach that can be applied for sentiment analysis. A dataset of 5,572 messages was tested using Word embedding Techniques such as Bag of words, Hashing, and Long short-term memory network Algorithm (LSTM). The results showed the proposed method performance are equal 98%, 93%, 95%, and 98% interns of precision, recall, F1-score, and accuracy respectively.
ISSN:2768-4644
DOI:10.1109/ECTIDAMTNCON53731.2022.9720349