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A LVQ-based neural network anti-spam email approach

Authors:

Zhan Chuan,

Lu Xianliang,

Hou Mengshu,

Zhou XuAuthors Info & Claims

ACM SIGOPS Operating Systems Review, Volume 39, Issue 1

Pages 34 - 39

https://doi.org/10.1145/1044552.1044555

Published: 01 January 2005 Publication History

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Abstract

Along with wide application of e-mail nowadays, many spam e-mails flood into people's email inboxes and bring catastrophe to their study and work. This paper presents a novel anti-spam e-mail filter based-LVQ network in terms of spam e-mails which are mainly made up of several kinds commercial or political spam emails at present. Our experiment has proved that the filter based on LVQ is superior to Bayes-based and BP-based approaches in total performances apparently.

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Cited By

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Bihl TPaciencia TBauer KTemple M(2020)Cyber-Physical Security with RF Fingerprint Classification through Distance Measure Extensions of Generalized Relevance Learning Vector QuantizationSecurity and Communication Networks10.1155/2020/39097632020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/3909763
Deniz EErbay HCosar M(2019)Classification of Turkish E-Mails with Doc2Vec2019 1st International Informatics and Software Engineering Conference (UBMYK)10.1109/UBMYK48245.2019.8965640(1-4)Online publication date: Nov-2019
https://doi.org/10.1109/UBMYK48245.2019.8965640
Faris HAl-Zoubi AHeidari AAljarah IMafarja MHassonah MFujita H(2019)An intelligent system for spam detection and identification of the most relevant features based on evolutionary Random Weight NetworksInformation Fusion10.1016/j.inffus.2018.08.00248(67-83)Online publication date: Aug-2019
https://doi.org/10.1016/j.inffus.2018.08.002
Show More Cited By

Index Terms

A LVQ-based neural network anti-spam email approach
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction
  2. World Wide Web
    1. Web applications
      1. Internet communications tools
        Email
    2. Web interfaces
      1. Browsers

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Published In

cover image ACM SIGOPS Operating Systems Review

ACM SIGOPS Operating Systems Review Volume 39, Issue 1

January 2005

93 pages

ISSN:0163-5980

DOI:10.1145/1044552

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Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 2005

Published in SIGOPS Volume 39, Issue 1

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Cited By

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Bihl TPaciencia TBauer KTemple M(2020)Cyber-Physical Security with RF Fingerprint Classification through Distance Measure Extensions of Generalized Relevance Learning Vector QuantizationSecurity and Communication Networks10.1155/2020/39097632020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/3909763
Deniz EErbay HCosar M(2019)Classification of Turkish E-Mails with Doc2Vec2019 1st International Informatics and Software Engineering Conference (UBMYK)10.1109/UBMYK48245.2019.8965640(1-4)Online publication date: Nov-2019
https://doi.org/10.1109/UBMYK48245.2019.8965640
Faris HAl-Zoubi AHeidari AAljarah IMafarja MHassonah MFujita H(2019)An intelligent system for spam detection and identification of the most relevant features based on evolutionary Random Weight NetworksInformation Fusion10.1016/j.inffus.2018.08.00248(67-83)Online publication date: Aug-2019
https://doi.org/10.1016/j.inffus.2018.08.002
Si JZhang YHu SSun LLi SYang HLi XWang Y(2018)Comparison of LVQ and BP Neural Network in the Diagnosis of Diabetes and RetinopathyData Science10.1007/978-981-13-2206-8_37(455-466)Online publication date: 9-Sep-2018
https://doi.org/10.1007/978-981-13-2206-8_37
Cabrera-León YGarcía Báez PSuárez-Araujo C(2018)E-Mail Spam Filter Based on Unsupervised Neural Architectures and Thematic Categories: Design and AnalysisComputational Intelligence10.1007/978-3-319-99283-9_12(239-262)Online publication date: 4-Oct-2018
https://doi.org/10.1007/978-3-319-99283-9_12
Ahanger T(2017)An effective approach of detecting DDoS using Artificial Neural Networks2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)10.1109/WiSPNET.2017.8299853(707-711)Online publication date: Mar-2017
https://doi.org/10.1109/WiSPNET.2017.8299853
Kaya YErtuğrul Ö(2016)A novel approach for spam email detection based on shifted binary patternsSecurity and Communication Networks10.1002/sec.14129:10(1216-1225)Online publication date: 10-Jul-2016
https://dl.acm.org/doi/10.1002/sec.1412
Jalab HSubramaniam TTaqa A(2015)Malay Language Text-Based Anti-Spam System Using Neural NetworkHandbook of Research on Threat Detection and Countermeasures in Network Security10.4018/978-1-4666-6583-5.ch013(242-253)Online publication date: 2015
https://doi.org/10.4018/978-1-4666-6583-5.ch013
Huang ZWeng CLi KCheng YLee C(2014)Deep learning vector quantization for acoustic information retrieval2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2014.6853817(1350-1354)Online publication date: May-2014
https://doi.org/10.1109/ICASSP.2014.6853817
Zitar RHamdan A(2013)Genetic optimized artificial immune system in spam detection: a review and a modelArtificial Intelligence Review10.1007/s10462-011-9285-z40:3(305-377)Online publication date: 1-Oct-2013
https://dl.acm.org/doi/10.1007/s10462-011-9285-z
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