Artificial Neural Network for Websites Classification with Phishing Characteristics

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ISSN Print: 2169-3285
ISSN Online: 2169-3323
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E-mail: sn@scirp.org

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"Artificial Neural Network for Websites Classification with Phishing Characteristics"
written by Ricardo Pinto Ferreira, Andréa Martiniano, Domingos Napolitano, Marcio Romero, Dacyr Dante De Oliveira Gatto, Edquel Bueno Prado Farias, Renato José Sassi,
published by Social Networking, Vol.7 No.2, 2018

has been cited by the following article(s):

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CrossRef

[1]	Role of artificial intelligence in chemistry
	Materials Today: Proceedings, 2022

[2]	Intelligent Deep Machine Learning Cyber Phishing URL Detection Based on BERT Features Extraction
	Electronics, 2022

[3]	ANN based approach to predict criminal trends in Bangladesh
	2022 2nd International Conference on …, 2022

[4]	Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis
	Fawa'reh, M Barhoush… - Cybernetics and …, 2022

[5]	Website Phishing Technique Classification Detection with HSSJAYA Based MLP Training
	Tehnički vjesnik, 2022

[6]	Machine Learning as a Data Science Tool to Predict Absenteeism for Factory Workers
	… on Data Analytics for Business and …, 2022

[7]	Malicious URLs detection using data streaming algorithms
	Jurnal Teknologi dan …, 2021

[8]	A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection
	Indones. J. Electr. Eng …, 2021

[9]	Rotation forest-based logistic model tree for website phishing detection
	Hamza… - … Science and Its …, 2021

[10]	Cascade generalization based functional tree for website phishing detection
	Advances in Cyber …, 2021

[11]	Phishing website detection from URLs using classical machine learning ANN model
	… 6–9, 2021, Proceedings, Part II …, 2021

[12]	Salp swarm optimization search based feature selection for enhanced phishing websites detection
	… 2021, Held as Part of EvoStar …, 2021

[13]	Optimized decision forest for website phishing detection
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[14]	Salp Swarm Optimization Search Based Feature Selection for Enhanced Phishing Websites Detection.
	2021

[15]	Phishing detection on tor hidden services
	2021

[16]	Comparison of the Bias and Weighting of Variables in Neural Networks (ANN) for the Selection of the Type of Housing in Spain and Mexico
	2021

[17]	Improving the phishing website detection using empirical analysis of Function Tree and its variants
	2021

[18]	Scope of Visual-Based Similarity Approach Using Convolutional Neural Network on Phishing Website Detection
	2021

[19]	Feature Selections for the Classification of Webpages to Detect Phishing Attacks: A Survey
	2020

[20]	Ai meta-learners and extra-trees algorithm for the detection of phishing websites
	2020

[21]	Web-Based Classification for Safer Browsing
	2020

[22]	Phishing Website Detection: Forest by Penalizing Attributes Algorithm and Its Enhanced Variations
	2020

[23]	Robust URL phishing detection based on deep learning
	Alyan, S Al-Ahmadi - KSII Transactions on Internet and …, 2020

[24]	Identification and Classification of Phishing Websites Using Machine Learning–Random Forest
	2019

[25]	Review of the machine learning methods in the classification of phishing attack
	2019

[26]	Kohonen maps to organize staff recruitment and study of workers' absenteeism
	2019

[27]	for Website Phishing Detection

[1]	ANN based approach to predict criminal trends in Bangladesh 2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP), 2022 DOI:10.1109/AISP53593.2022.9760684

[2]	Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis Cybernetics and Information Technologies, 2022 DOI:10.2478/cait-2022-0004

[3]	Intelligent Deep Machine Learning Cyber Phishing URL Detection Based on BERT Features Extraction Electronics, 2022 DOI:10.3390/electronics11223647

[4]	Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis Cybernetics and Information Technologies, 2022 DOI:10.2478/cait-2022-0004

[5]	Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis Cybernetics and Information Technologies, 2022 DOI:10.2478/cait-2022-0004

[6]	Machine Learning as a Data Science Tool to Predict Absenteeism for Factory Workers 2022 International Conference on Data Analytics for Business and Industry (ICDABI), 2022 DOI:10.1109/ICDABI56818.2022.10041623

[7]	Role of artificial intelligence in chemistry Materials Today: Proceedings, 2022 DOI:10.1016/j.matpr.2021.09.428

[8]	Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis Cybernetics and Information Technologies, 2022 DOI:10.2478/cait-2022-0004

[9]	Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis Cybernetics and Information Technologies, 2022 DOI:10.2478/cait-2022-0004

[10]	Malicious URLs detection using data streaming algorithms Jurnal Teknologi dan Sistem Komputer, 2021 DOI:10.14710/jtsiskom.2021.13965

[11]	Improving the phishing website detection using empirical analysis of Function Tree and its variants Heliyon, 2021 DOI:10.1016/j.heliyon.2021.e07437

[12]	Data Science and Intelligent Systems Lecture Notes in Networks and Systems, 2021 DOI:10.1007/978-3-030-90321-3_47

[13]	Advances in Cyber Security Communications in Computer and Information Science, 2021 DOI:10.1007/978-981-16-8059-5_17

[14]	Computational Methods and Data Engineering Advances in Intelligent Systems and Computing, 2021 DOI:10.1007/978-981-15-6876-3_9

[15]	Intelligent System Design Advances in Intelligent Systems and Computing, 2021 DOI:10.1007/978-981-15-5400-1_45

[16]	Applications of Evolutionary Computation Lecture Notes in Computer Science, 2021 DOI:10.1007/978-3-030-72699-7_10

[17]	Machine Intelligence and Data Analytics for Sustainable Future Smart Cities Studies in Computational Intelligence, 2021 DOI:10.1007/978-3-030-72065-0_2

[18]	Computational Science and Its Applications – ICCSA 2021 Lecture Notes in Computer Science, 2021 DOI:10.1007/978-3-030-87013-3_12

[19]	Improving the phishing website detection using empirical analysis of Function Tree and its variants Heliyon, 2021 DOI:10.1016/j.heliyon.2021.e07437

[20]	Security and Privacy in Communication Networks Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2021 DOI:10.1007/978-3-030-90022-9_28

[21]	Feature Selections for the Classification of Webpages to Detect Phishing Attacks: A Survey 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), 2020 DOI:10.1109/HORA49412.2020.9152934

[22]	Phishing Website Detection: Forest by Penalizing Attributes Algorithm and Its Enhanced Variations Arabian Journal for Science and Engineering, 2020 DOI:10.1007/s13369-020-04802-1

[23]	AI Meta-Learners and Extra-Trees Algorithm for the Detection of Phishing Websites IEEE Access, 2020 DOI:10.1109/ACCESS.2020.3013699

[24]	Kohonen maps to organize staff recruitment and study of workers’ absenteeism Journal of Physics: Conference Series, 2019 DOI:10.1088/1742-6596/1399/3/033108

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