A deep learning method for automatic <scp>SMS</scp> spam classification: Performance of learning algorithms on indigenous dataset-Reference-Cited by-同舟云学术

A deep learning method for automatic SMS spam classification: Performance of learning algorithms on indigenous dataset

Published:2022-04 Issue:17 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Abayomi‐Alli Olusola¹^ORCID,Misra Sanjay²^ORCID,Abayomi‐Alli Adebayo³^ORCID

Affiliation:

1. Department of Software Engineering Kaunas University of Technology Kaunas Lithuania

2. Department of Computer Science and Communication Østfold University College Halden Norway

3. Department of Computer Science Federal University of Agriculture Abeokuta Nigeria

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6989

Reference61 articles.

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3. TruSMS: A trustworthy SMS spam control system based on trust management

4. Cloudmark.SMS spam overview; 2013. Accessed 13 February 2014.https://www.cloudmark.com/en/s/¨./whitepapers/sms‐spam‐overview

5. BothaJ VantWC LeenenL.A comparison of chat applications in terms of security and privacy. Proceedings of the 18th European Conference on Cyber Warfare and Security; July 2019:55.

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