A Multi-Classifier Based Prediction Model for Phishing Emails Detection Using Topic Modelling, Named Entity Recognition and Image Processing

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Circuits and Systems

ISSN Print: 2153-1285
ISSN Online: 2153-1293
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"A Multi-Classifier Based Prediction Model for Phishing Emails Detection Using Topic Modelling, Named Entity Recognition and Image Processing"
written by C. Emilin Shyni, S. Sarju, S. Swamynathan,
published by Circuits and Systems, Vol.7 No.9, 2016

has been cited by the following article(s):

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[6]	Email & Fraud Protection con tecnologie open source= Email & Fraud Protection with open source technologies
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[8]	Detection of Phishing Website Using Intelligent Machine Learning Classifiers
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[9]	A systematic literature review on phishing email detection using natural language processing techniques
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[10]	A systematic literature review on phishing email detection using natural
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[11]	Addressing Cyber Deception and Abuse from a Human Factors Perspective
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[13]	Lumen: A Machine Learning Framework to Expose Influence Cues in Text
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[14]	TREND ANALYSIS IN AI RESEARCH OVER TIME USING NLP TECHNIQUES
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[15]	Detekcia foriem sociálneho inžinierstva v emailovej komunikácii
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[16]	Phishing Detection in E-mails using Machine Learning
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[17]	Detekce phishingových emailů s využitím rozpoznávání pojmenovaných entit
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[1]	Enhancing phishing email detection with stylometric features and classifier stacking International Journal of Information Security, 2025 DOI:10.1007/s10207-024-00928-7

[2]	Deep Sciences for Computing and Communications Communications in Computer and Information Science, 2024 DOI:10.1007/978-3-031-68905-5_31

[3]	Artificial Intelligence, Data Science and Applications Lecture Notes in Networks and Systems, 2024 DOI:10.1007/978-3-031-48573-2_35

[4]	A Review of Different Content-Based Phishing Email Detection Methods 2023 9th International Engineering Conference on Sustainable Technology and Development (IEC), 2023 DOI:10.1109/IEC57380.2023.10438812

[5]	Soft Computing and Signal Processing Smart Innovation, Systems and Technologies, 2023 DOI:10.1007/978-981-19-8669-7_3

[6]	A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3183083

[7]	A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3183083

[8]	Lumen: A machine learning framework to expose influence cues in texts Frontiers in Computer Science, 2022 DOI:10.3389/fcomp.2022.929515

[9]	Phishing Detection in E-mails using Machine Learning 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), 2022 DOI:10.1109/ICTACS56270.2022.9987839

[10]	Phishing Detection in E-mails using Machine Learning 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), 2022 DOI:10.1109/ICTACS56270.2022.9987839

[11]	HTIE: A Hierarchical Task Identification Framework for E-mails 2021 IEEE Seventh International Conference on Big Data Computing Service and Applications (BigDataService), 2021 DOI:10.1109/BigDataService52369.2021.00015

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