On the public citation graph
A Survey of Machine Learning-Based Solutions for Phishing Website Detection
0 signed · 226 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-981-33-6835-4_41openalex-snapshot
Ensemble-Based Logistic Model Trees for Website Phishing Detection
inferredcites →https://doi.org/10.1007/s00521-013-1490-zopenalex-snapshot
Predicting phishing websites based on self-structuring neural network
inferredcites →https://doi.org/10.1007/s11042-021-10678-6openalex-snapshot
ISHO: improved spotted hyena optimization algorithm for phishing website detection
inferredcites →https://doi.org/10.1007/s11235-020-00733-2openalex-snapshot
A comprehensive survey of AI-enabled phishing attacks detection techniques
inferredcites →https://doi.org/10.1007/s11235-020-00739-wopenalex-snapshot
Phishing website detection using support vector machines and nature-inspired optimization algorithms
inferredcites →https://doi.org/10.1007/s11277-021-08196-7openalex-snapshot
Smart Phishing Detection in Web Pages using Supervised Deep Learning Classification and Optimization Technique ADAM
inferredcites →https://doi.org/10.1016/j.comcom.2021.04.023openalex-snapshot
A novel approach for phishing URLs detection using lexical based machine learning in a real-time environment
inferredcites →https://doi.org/10.1016/j.cose.2015.07.006openalex-snapshot
Utilisation of website logo for phishing detection
inferredcites →https://doi.org/10.1016/j.cose.2020.102123openalex-snapshot
Intelligent cyber-phishing detection for online
inferredcites →https://doi.org/10.1016/j.dss.2016.05.005openalex-snapshot
PhishWHO: Phishing webpage detection via identity keywords extraction and target domain name finder
inferredcites →https://doi.org/10.1016/j.eswa.2020.113863openalex-snapshot
An improved ELM-based and data preprocessing integrated approach for phishing detection considering comprehensive features
inferredcites →https://doi.org/10.1016/s1361-3723(19)30025-9openalex-snapshot
APWG: Phishing Activity Trends Report Q4 2018
inferredcites →https://doi.org/10.1049/iet-ifs.2019.0006openalex-snapshot
Hybrid intelligent phishing website prediction using deep neural networks with genetic algorithm‐based feature selection and weighting
inferredcites →https://doi.org/10.1049/iet-net.2020.0078openalex-snapshot
Web phishing detection techniques: a survey on the state‐of‐the‐art, taxonomy and future directions
inferredcites →https://doi.org/10.1080/01969722.2020.1826659openalex-snapshot
Improving Spoofed Website Detection Using Machine Learning
inferredcites →https://doi.org/10.1080/17517575.2021.1896786openalex-snapshot
A survey of phishing attack techniques, defence mechanisms and open research challenges
inferredcites →https://doi.org/10.1080/23742917.2020.1813396openalex-snapshot
Phishing website detection based on effective machine learning approach
inferredcites →https://doi.org/10.1108/el-05-2019-0118openalex-snapshot
Phishing web site detection using diverse machine learning algorithms
inferredcites →https://doi.org/10.1109/access.2020.3013699openalex-snapshot
AI Meta-Learners and Extra-Trees Algorithm for the Detection of Phishing Websites
inferredcites →https://doi.org/10.1109/fuzz-ieee.2019.8858884openalex-snapshot
Fuzzy Rough Set Feature Selection to Enhance Phishing Attack Detection
inferredcites →https://doi.org/10.1109/icaccs48705.2020.9074400openalex-snapshot
Phishing Website Detection Based on Machine Learning: A Survey
inferredcites →https://doi.org/10.1109/icais50930.2021.9395810openalex-snapshot
Phishing website detection using novel machine learning fusion approach
inferredcites →https://doi.org/10.1109/icdcs.2016.10openalex-snapshot
Know Your Phish: Novel Techniques for Detecting Phishing Sites and Their Targets
inferredcites →https://doi.org/10.1109/icdcs.2016.44openalex-snapshot
Real-Time Client-Side Phishing Prevention Add-On
inferredcites →https://doi.org/10.1109/icecta.2017.8252051openalex-snapshot
Intelligent phishing website detection using random forest classifier
inferredcites →https://doi.org/10.1109/icsem.2010.14openalex-snapshot
Feature Selection Using Principal Component Analysis
inferredcites →https://doi.org/10.1145/3227609.3227655openalex-snapshot
Swarm Intelligence Approaches for Parameter Setting of Deep Learning Neural Network
inferredcites →https://doi.org/10.1155/2019/2595794openalex-snapshot
PDRCNN: Precise Phishing Detection with Recurrent Convolutional Neural Networks
inferredcites →https://doi.org/10.1186/s13635-016-0034-3openalex-snapshot
A novel approach to protect against phishing attacks at client side using auto-updated white-list
inferredcites →https://doi.org/10.1186/s42400-020-00059-1openalex-snapshot
Development of anti-phishing browser based on random forest and rule of extraction framework
inferredcites →https://doi.org/10.14569/ijacsa.2020.0110477openalex-snapshot
Feature Selection for Phishing Website Classification
inferredcites →https://doi.org/10.17632/h3cgnj8hft.1openalex-snapshot
Phishing Dataset for Machine Learning: Feature Evaluation
inferredcites →https://doi.org/10.17762/turcomat.v12i7.3638openalex-snapshot
Phishing Website Detection Using Novel Features And Machine Learning Approach
inferredcites →https://doi.org/10.21608/mjeer.2020.32404.1021openalex-snapshot
A Smart Model for Web Phishing Detection Based on New Proposed Feature Selection Technique
inferredcites →https://doi.org/10.21608/mjeer.2021.146286openalex-snapshot
A Smart Model for Web Phishing Detection Based on New Proposed Feature Selection Technique
inferredcites →https://doi.org/10.3390/electronics9091514openalex-snapshot
An Effective Phishing Detection Model Based on Character Level Convolutional Neural Network from URL
inferredcites →https://doi.org/10.3991/ijim.v13i10.10797openalex-snapshot
Mobile Phishing Websites Detection and Prevention Using Data Mining Techniques
inferredcites →https://doi.org/10.48550/arxiv.2103.12739openalex-snapshot
Detecting Phishing Sites -- An Overview
inferredcites →https://doi.org/10.5455/jjcit.71-1600061738openalex-snapshot
PhiBoost- A novel phishing detection model Using Adaptive Boosting approach
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/ett.70119openalex-snapshot
A Concise Survey on Modern Web‐Based Phishing Techniques and Advanced Mitigation Strategies
inferred← citeshttps://doi.org/10.1007/978-3-030-98741-1_40openalex-snapshot
Catching a Phish: Frontiers of Deep Learning-Based Anticipating Detection Engines
inferred← citeshttps://doi.org/10.1007/978-3-031-24475-9_61openalex-snapshot
Phishing Website Detection with and Without Proper Feature Selection Techniques: Machine Learning Approach
inferred← citeshttps://doi.org/10.1007/978-3-031-25088-0_47openalex-snapshot
Randomized Active Learning to Identify Phishing URL
inferred← citeshttps://doi.org/10.1007/978-3-031-28451-9_21openalex-snapshot
Detection of Malicious Sites Using Graph Machine Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-56326-3_20openalex-snapshot
MADONNA: Browser-Based MAlicious Domain Detection Through Optimized Neural Network with Feature Analysis
inferred← citeshttps://doi.org/10.1007/978-3-031-59100-6_12openalex-snapshot
A Survey of Machine Learning Techniques in Phishing Detection
inferred← citeshttps://doi.org/10.1007/978-3-031-62624-1_4openalex-snapshot
Performance Analysis of Classifying URL Phishing Using Recursive Feature Elimination
inferred← citeshttps://doi.org/10.1007/978-3-031-74127-2_43openalex-snapshot
Advancing Phishing Attack Detection with a Novel Dataset and Deep Learning Solution
inferred← citeshttps://doi.org/10.1007/978-3-031-79086-7_26openalex-snapshot
A Review of a Website Phishing Detection Taxonomy
inferred← citeshttps://doi.org/10.1007/978-3-031-97713-8_13openalex-snapshot
Phishing Site Analyzer: AI-Driven Real-Time Detection with MLP and Flask
inferred← citeshttps://doi.org/10.1007/978-3-031-97992-7_43openalex-snapshot
A Lightweight Heuristic Method for Phishing Website Detection
inferred← citeshttps://doi.org/10.1007/978-3-032-03072-6_20openalex-snapshot
Development of an Algorithmic Model of Access Management Based on Phishing Detection
inferred← citeshttps://doi.org/10.1007/978-3-032-14350-1_4openalex-snapshot
PhishBuster: Phishing Detection Based on URL Embeddings and Deep Learning Models with Explainability
inferred← citeshttps://doi.org/10.1007/978-3-032-28379-5_47openalex-snapshot
An Explainable Hybrid Natural Language Processing and CatBoost Framework for Phishing Website Detection
inferred← citeshttps://doi.org/10.1007/978-3-032-33535-7_40openalex-snapshot
A Hybrid TF-IDF and Machine Learning Approach for SMS Spam Detection with Data Augmentation and Statistical Validation
inferred← citeshttps://doi.org/10.1007/978-981-95-0148-9_33openalex-snapshot
AI-Powered Cyber Sentinel: Advanced Phishing Website Detection for Enhanced Online Security
inferred← citeshttps://doi.org/10.1007/978-981-95-9843-4_38openalex-snapshot
Enhancing Security in Intelligent Hotel Ecosystems Using AI-Based Phishing Detection
inferred← citeshttps://doi.org/10.1007/978-981-96-0573-6_17openalex-snapshot
“Is this Site Legit?”: LLMs for Scam Website Detection
inferred← citeshttps://doi.org/10.1007/978-981-96-4148-2_16openalex-snapshot
Enhanced Phishing Detection Using LSTM, CNN, and SVM Techniques
inferred← citeshttps://doi.org/10.1007/978-981-96-9650-5_56openalex-snapshot
URL Phishing Detection with Exploratory Data Analysis for Secure Customer Communication
inferred← citeshttps://doi.org/10.1007/978-981-97-4149-6_17openalex-snapshot
Efficient Malicious Website Detection Technique Using Stacking Ensemble of Machine Learning Models
inferred← citeshttps://doi.org/10.1007/978-981-97-6318-4_26openalex-snapshot
Machine-Learning-Driven Detection of Malicious Emails and Fake Websites
inferred← citeshttps://doi.org/10.1007/978-981-97-7423-4_14openalex-snapshot
A Systemic Review of Machine Learning Approaches for Malicious URL Detection
inferred← citeshttps://doi.org/10.1007/978-981-99-0769-4_27openalex-snapshot
Identification of Spoofing URLs Using Hybrid Algorithms
inferred← citeshttps://doi.org/10.1007/978-981-99-1620-7_12openalex-snapshot
Deep Learning-Based Framework for URL Phishing Detection
inferred← citeshttps://doi.org/10.1007/s10207-025-00992-7openalex-snapshot
Large language models for software vulnerability detection: a guide for researchers on models, methods, techniques, datasets, and metrics
inferred← citeshttps://doi.org/10.1007/s10207-025-01157-2openalex-snapshot
Enhanced phishing detection using binary encoding XGBoost and LSTM feature extraction and capsule network classification
inferred← citeshttps://doi.org/10.1007/s10586-024-04272-2openalex-snapshot
Spark-based multi-verse optimizer as wrapper features selection algorithm for phishing attack challenge
inferred← citeshttps://doi.org/10.1007/s10586-025-05896-8openalex-snapshot
An enhanced deep learning model for phishing detection based on bayesian optimization and hybrid CNN VGG19 model
inferred← citeshttps://doi.org/10.1007/s11042-023-14731-4openalex-snapshot
Intelligent phishing website detection using machine learning
inferred← citeshttps://doi.org/10.1007/s40745-022-00379-8openalex-snapshot
Modeling Hybrid Feature-Based Phishing Websites Detection Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2025.110212openalex-snapshot
Development of BiLSTM deep learning model to detect URL-based phishing attacks
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2026.111001openalex-snapshot
Real-time phishing uniform resource locator detection based on hybrid embedding transformer and retraining-free inferencing
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2026.111186openalex-snapshot
A comprehensive review of malicious URLs: Detection techniques, features and datasets
inferred← citeshttps://doi.org/10.1016/j.cose.2025.104371openalex-snapshot
MADONNA: Browser-based malicious domain detection using Optimized Neural Network by leveraging AI and feature analysis
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122199openalex-snapshot
Anti-phishing: A comprehensive perspective
inferred← citeshttps://doi.org/10.1016/j.fraope.2026.100579openalex-snapshot
Ensemble transfer learning for cross-dataset phishing detection
inferred← citeshttps://doi.org/10.1016/j.neucom.2023.126327openalex-snapshot
Deep neural networks in the cloud: Review, applications, challenges and research directions
inferred← citeshttps://doi.org/10.1016/j.patcog.2026.114343openalex-snapshot
Ethereum phishing fraud detection via dynamic graph neural network with anonymous walks
inferred← citeshttps://doi.org/10.1016/j.procs.2024.12.031openalex-snapshot
Advanced Phishing Website Detection with SMOTETomek-XGB: Addressing Class Imbalance for Optimal Results
inferred← citeshttps://doi.org/10.1016/j.procs.2026.06.541openalex-snapshot
Phishing URL Detection in Real-Time: Machine Learning and Deep Learning Approaches on a Custom Threat Intelligence Dataset
inferred← citeshttps://doi.org/10.1038/s41598-025-21384-wopenalex-snapshot
Phishing detection on webpages in European non-English languages based on machine learning
inferred← citeshttps://doi.org/10.1038/s41598-025-33568-5openalex-snapshot
Understanding phishing discussions on stack overflow and information security stack exchange
inferred← citeshttps://doi.org/10.1049/ise2.12106openalex-snapshot
An enhanced deep learning‐based phishing detection mechanism to effectively identify malicious URLs using variational autoencoders
inferred← citeshttps://doi.org/10.1049/ise2/2558485openalex-snapshot
Detecting Phishing Emails Using GloVe Word Embeddings and Ensemble Machine Learning Model
inferred← citeshttps://doi.org/10.1051/itmconf/20235701008openalex-snapshot
Detecting Phishing Websites using recent Techniques: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1051/itmconf/20257802010openalex-snapshot
Analysis on Phishing Detection Methods
inferred← citeshttps://doi.org/10.1063/5.0170633openalex-snapshot
A deep intelligence-based face spoofing liveness recognition in pandemic
inferred← citeshttps://doi.org/10.1063/5.0277817openalex-snapshot
Comparative analysis of the adaptation of cookie guard with Rivest-Shamir-Adleman encryption using random forest and histogram-based outlier score
inferred← citeshttps://doi.org/10.1063/5.0285967openalex-snapshot
Malicious URL detection using machine learning
inferred← citeshttps://doi.org/10.1063/5.0317813openalex-snapshot
Advancing web security: Analysis of machine learning algorithms in detection of phishing websites
inferred← citeshttps://doi.org/10.1080/19361610.2025.2508726openalex-snapshot
A Survey on Phishing Attack Taxonomy, Detection Techniques, Datasets, and Security Measures
inferred← citeshttps://doi.org/10.1109/access.2021.3137636openalex-snapshot
A Deep Learning-Based Framework for Phishing Website Detection
inferred← citeshttps://doi.org/10.1109/access.2022.3151903openalex-snapshot
Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions
inferred← citeshttps://doi.org/10.1109/access.2022.3183083openalex-snapshot
A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques
inferred← citeshttps://doi.org/10.1109/access.2023.3237798openalex-snapshot
A Survey of Intelligent Detection Designs of HTML URL Phishing Attacks
inferred← citeshttps://doi.org/10.1109/access.2024.3436812openalex-snapshot
A Study on Adversarial Sample Resistance and Defense Mechanism for Multimodal Learning-Based Phishing Website Detection
inferred← citeshttps://doi.org/10.1109/access.2024.3491429openalex-snapshot
Multi-Modal Comparative Analysis on Execution of Phishing Detection Using Artificial Intelligence
inferred← citeshttps://doi.org/10.1109/access.2024.3514972openalex-snapshot
A State-of-the-Art Review on Phishing Website Detection Techniques
inferred← citeshttps://doi.org/10.1109/africon55910.2023.10293475openalex-snapshot
Detecting Phishing Attacks Using Feature Importance-Based Machine Learning Approach
inferred← citeshttps://doi.org/10.1109/aimla67915.2026.11521080openalex-snapshot
Enhanced Phishing Detection Using Gradient Boosting Classifier: A Machine Learning Approach
inferred← citeshttps://doi.org/10.1109/amict65811.2025.11402780openalex-snapshot
Enhancing Phishing Detection Through Machine Learning
inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11401440openalex-snapshot
PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11402049openalex-snapshot
Phishing Defense: An ML-Based URL Detection System with Real-World Deployment
inferred← citeshttps://doi.org/10.1109/ccwc62904.2025.10903847openalex-snapshot
GPT-4 Meets TF-IDF: A Hybrid Approach for Detecting Spam Emails Using Machine Learning
inferred← citeshttps://doi.org/10.1109/comst.2024.3441752openalex-snapshot
Phishing Webpage Detection: Unveiling the Threat Landscape and Investigating Detection Techniques
inferred← citeshttps://doi.org/10.1109/confluence60223.2024.10463281openalex-snapshot
CyberGuard - Guarding Against Deceptive Websites
inferred← citeshttps://doi.org/10.1109/csdgais64098.2024.11064828openalex-snapshot
Augmented Framework for Enhanced Phishing Detection and Prevention
inferred← citeshttps://doi.org/10.1109/csr57506.2023.10224924openalex-snapshot
VulDetect: A novel technique for detecting software vulnerabilities using Language Models
inferred← citeshttps://doi.org/10.1109/cvmi61877.2024.10782525openalex-snapshot
A Comparative Analysis of Traditional Machine Learning, Deep Learning and Boosting Algorithms on Phishing URL Detection
inferred← citeshttps://doi.org/10.1109/ecrime66200.2024.00008openalex-snapshot
Owned, Pwned or Rented: Whose Domain Is It?
inferred← citeshttps://doi.org/10.1109/emergin63207.2024.10961019openalex-snapshot
Advanced Threat Detection: Leveraging Data Analytics for Cybersecurity Enhancement
inferred← citeshttps://doi.org/10.1109/emergin63207.2024.10961806openalex-snapshot
A Deep Learning Based Improved Detection for Phishing Attacks in Social Engines
inferred← citeshttps://doi.org/10.1109/emes65692.2025.11045637openalex-snapshot
Comparison of Machine Learning Algorithms Used for Phishing Detection
inferred← citeshttps://doi.org/10.1109/ic3se62002.2024.10592901openalex-snapshot
Phishing Websites Classification using Extreme Learning Machine
inferred← citeshttps://doi.org/10.1109/ic3se62002.2024.10593139openalex-snapshot
Examination of Phishing Attempts on Web-Based Business Applications and Their Preventions
inferred← citeshttps://doi.org/10.1109/icac3n56670.2022.10074337openalex-snapshot
Phishing URL Detection Using Machine Learning: A Survey
inferred← citeshttps://doi.org/10.1109/icaic60265.2024.10433827openalex-snapshot
Deep Reinforcement Learning-based Malicious URL Detection with Feature Selection
inferred← citeshttps://doi.org/10.1109/icaic60265.2024.10433842openalex-snapshot
A Holistic Review on Detection of Malicious Browser Extensions and Links using Deep Learning
inferred← citeshttps://doi.org/10.1109/icaiihi57871.2023.10489233openalex-snapshot
Detection of Healthcare Phishing Websites Using Machine Learning
inferred← citeshttps://doi.org/10.1109/icbats66542.2025.11258475openalex-snapshot
AI-Driven Prediction Model for Phishing Website Detection
inferred← citeshttps://doi.org/10.1109/icbir61386.2024.10875056openalex-snapshot
Machine-Learned Defense Mechanism Against Phishing URL Exploitation for User Protection
inferred← citeshttps://doi.org/10.1109/icces63552.2024.10859402openalex-snapshot
Enhancing Cybersecurity using Machine Learning Strategies for Phishing Defense
inferred← citeshttps://doi.org/10.1109/iccit63348.2025.10989468openalex-snapshot
PhishingWebsite URL's Detection Using Machine Learning
inferred← citeshttps://doi.org/10.1109/iccr67387.2025.11292212openalex-snapshot
Recognizing Phishing in Emails by Using Natural Language Processing & Machine Learning Techniques
inferred← citeshttps://doi.org/10.1109/iccrtee64519.2025.11053024openalex-snapshot
Towards Practical Phishing Detection: Addressing Challenges with Hybrid Machine Learning Architectures
inferred← citeshttps://doi.org/10.1109/icdca69396.2026.11620472openalex-snapshot
Deep Learning-Based Multi-Class Website Text Classification Using Bi-LSTM Networks
inferred← citeshttps://doi.org/10.1109/icdcece53908.2022.9793225openalex-snapshot
An Awareness About Phishing Attack And Fake News Using Machine Learning Technique
inferred← citeshttps://doi.org/10.1109/icecaa55415.2022.9936112openalex-snapshot
CNN based Prediction Analysis for Web Phishing Prevention
inferred← citeshttps://doi.org/10.1109/icest66328.2025.11098240openalex-snapshot
Machine Learning Approaches for Phishing Detection Using URL Analysis
inferred← citeshttps://doi.org/10.1109/iceta61311.2023.10343937openalex-snapshot
Eye-Tracking System as a Part of the Phishing Training
inferred← citeshttps://doi.org/10.1109/icidca66325.2025.11280568openalex-snapshot
BERT-based Semantic Matching for Detecting Phishing URLs in Email Content
inferred← citeshttps://doi.org/10.1109/icirca54612.2022.9985744openalex-snapshot
A Survey and Taxonomy of Anti-Phishing Techniques for Detecting Fake Websites
inferred← citeshttps://doi.org/10.1109/icmi65310.2025.11139844openalex-snapshot
A Robust Voting-ML System in Identifying Phishing Websites Using Hybrid Ensemble Learning and Advanced Feature Selection Techniques
inferred← citeshttps://doi.org/10.1109/icnisc57059.2022.00034openalex-snapshot
A Phishing Website Detection Method Based on Multi-layer Perceptron with Mutual Information Feature Selection
inferred← citeshttps://doi.org/10.1109/icocseti63724.2025.11019127openalex-snapshot
Detecting Phising Website using Machine Learning Methods
inferred← citeshttps://doi.org/10.1109/icodsa53588.2021.9617482openalex-snapshot
Detection of Phising Websites using Machine Learning Approaches
inferred← citeshttps://doi.org/10.1109/icodse68111.2025.11351605openalex-snapshot
Enhancing Phishing Detection with Machine Learning: A Study on the Effectiveness of Feature Selection Techniques
inferred← citeshttps://doi.org/10.1109/icoiact67584.2025.11345072openalex-snapshot
A Comparative Study of Phishing Link Detection Algorithms Using Hybrid and Non-Hybrid Approaches
inferred← citeshttps://doi.org/10.1109/icscds56580.2023.10104988openalex-snapshot
A Comprehensive Survey of Automated Website Phishing Detection Techniques: A Perspective of Artificial Intelligence and Human Behaviors
inferred← citeshttps://doi.org/10.1109/icses63445.2024.10763142openalex-snapshot
Phishing Attack Prediction using Several Machine Learning Techniques
inferred← citeshttps://doi.org/10.1109/icsist70215.2026.11705888openalex-snapshot
An Intelligent TabNet-based Framework for Phishing Website Detection using URL and Webpage Features
inferred← citeshttps://doi.org/10.1109/icssas57918.2023.10331880openalex-snapshot
A Hybrid Transformer Ensemble Approach for Phishing Website Detection
inferred← citeshttps://doi.org/10.1109/icvadv63329.2025.10961925openalex-snapshot
Phishing URL Detection Using Naive Bayes Classification: A Robust Method for Accurate Detection
inferred← citeshttps://doi.org/10.1109/incoft55651.2022.10094539openalex-snapshot
Spoofing URL Detection
inferred← citeshttps://doi.org/10.1109/innocomp63224.2024.00020openalex-snapshot
PHISHWATCH: EMPOWERING USERS WITH EFFECTIVE PHISHING DETECTION TECHNIQUES
inferred← citeshttps://doi.org/10.1109/iscs61804.2024.10581192openalex-snapshot
Enhanced Phishing URL Detection through Stacked Machine Learning Model
inferred← citeshttps://doi.org/10.1109/isiber68248.2026.11470168openalex-snapshot
Classification of Phishing Mail Detection Using Hybrid Approach of Fusion Model
inferred← citeshttps://doi.org/10.1109/ismsit67332.2025.11268031openalex-snapshot
Phishing Detection Framework and Cybersecurity Effectiveness during COVID-19 pandemic: A Technical Review
inferred← citeshttps://doi.org/10.1109/ist64061.2024.10843500openalex-snapshot
Detection of Phishing Attacks in Iranian E-Banking Websites Using a Neuro-Fuzzy System
inferred← citeshttps://doi.org/10.1109/jiot.2025.3554788openalex-snapshot
Protecting Virtual Economies: A Blockchain-Based Anti-Phishing Authentication Protocol for Metaverse Applications
inferred← citeshttps://doi.org/10.1109/jproc.2024.3379855openalex-snapshot
Internet-Based Social Engineering Psychology, Attacks, and Defenses: A Survey
inferred← citeshttps://doi.org/10.1109/kse63888.2024.11063532openalex-snapshot
Graphish: Advanced Phishing URL Detection via Graph-Based Embeddings
inferred← citeshttps://doi.org/10.1109/nkcon56289.2022.10126569openalex-snapshot
Stop Phishing : Master Anti-Phishing Techniques
inferred← citeshttps://doi.org/10.1109/ojcoms.2024.3462503openalex-snapshot
Across the Spectrum In-Depth Review AI-Based Models for Phishing Detection
inferred← citeshttps://doi.org/10.1109/peccii70991.2026.11662028openalex-snapshot
TriGuard: LightGBM, XGBoost, and Random Forest Hybrid ensemble framework against intelligent malicious URL detection
inferred← citeshttps://doi.org/10.1109/seb4sdg60871.2024.10629721openalex-snapshot
Stack Ensemble Model For Detection Of Phishing Website
inferred← citeshttps://doi.org/10.1109/snams67467.2025.11391188openalex-snapshot
Evaluating Machine Learning Models for Phishing Detection in Cybersecurity
inferred← citeshttps://doi.org/10.1109/tce.2024.3404459openalex-snapshot
Advanced Learning for Phishing URLs Detection to Secure Consumer-Centric Applications
inferred← citeshttps://doi.org/10.1109/tocs56154.2022.10016193openalex-snapshot
A survey of phishing detection: from an intelligent countermeasures view
inferred← citeshttps://doi.org/10.1145/3564625.3567980openalex-snapshot
SpacePhish: The Evasion-space of Adversarial Attacks against Phishing Website Detectors using Machine Learning
inferred← citeshttps://doi.org/10.1145/3589334.3645502openalex-snapshot
"Are Adversarial Phishing Webpages a Threat in Reality?" Understanding the Users' Perception of Adversarial Webpages
inferred← citeshttps://doi.org/10.1145/3605764.3623920openalex-snapshot
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors
inferred← citeshttps://doi.org/10.1145/3626232.3653283openalex-snapshot
WikiPhish: A Diverse Wikipedia-Based Dataset for Phishing Website Detection: Data/Toolset Paper
inferred← citeshttps://doi.org/10.1145/3638253openalex-snapshot
Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks against Phishing Website Detectors Using Machine Learning
inferred← citeshttps://doi.org/10.1145/3658644.3690348openalex-snapshot
Content, Nudges and Incentives: A Study on the Effectiveness and Perception of Embedded Phishing Training
inferred← citeshttps://doi.org/10.11591/ijece.v14i3.pp3021-3035openalex-snapshot
Real-time phishing detection using deep learning methods by extensions
inferred← citeshttps://doi.org/10.11591/ijeecs.v33.i1.pp269-277openalex-snapshot
Deep neural networks approach with transfer learning to detect fake accounts social media on Twitter
inferred← citeshttps://doi.org/10.1177/18724981251366763openalex-snapshot
Machine learning techniques for phishing detection: A review of methods, challenges, and future directions
inferred← citeshttps://doi.org/10.1186/s40537-025-01174-xopenalex-snapshot
Leveraging machine learning to proactively identify phishing campaigns before they strike
inferred← citeshttps://doi.org/10.13052/jwe1540-9589.2251openalex-snapshot
HCNN-LSTM: Hybrid Convolutional Neural Network with Long Short-Term Memory Integrated for Legitimate Web Prediction
inferred← citeshttps://doi.org/10.14445/23488379/ijeee-v10i4p114openalex-snapshot
Improved Random Forest Algorithm using Chicken Swarm Optimization for Phishing Website Classification Model
inferred← citeshttps://doi.org/10.14710/transmisi.26.3.114-121openalex-snapshot
ENHANCING BANK CUSTOMER PROTECTION AGAINST PHISHING ATTACKS THROUGH XGBOOST-BASED FEATURE ANALYSIS
inferred← citeshttps://doi.org/10.17485/ijst/v16i29.1500openalex-snapshot
A Novel Hybrid Feature Extraction Technique and Spam Review Detection using Ensemble Machine Learning Algorithm by Web Scrapping
inferred← citeshttps://doi.org/10.18488/76.v9i1.2983openalex-snapshot
Machine Learning and Deep Learning Based Phishing Websites Detection: The Current Gaps and Next Directions
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2518632/v1openalex-snapshot
Intelligent Methods in Phishing Website Detection: A Systematic Literature Review
inferred← citeshttps://doi.org/10.21203/rs.3.rs-7959785/v1openalex-snapshot
A Hybrid Deep Ensemble Framework with Interpretability for Phishing URL Detection
inferred← citeshttps://doi.org/10.2197/ipsjjip.32.298openalex-snapshot
JABBERWOCK: A Tool for WebAssembly Dataset Generation and Its Application to Malicious Website Detection
inferred← citeshttps://doi.org/10.22161/ijaems.910.2openalex-snapshot
Deep Learning Neural Networks in the Cloud
inferred← citeshttps://doi.org/10.24294/jipd8848openalex-snapshot
Identifying suspicious internet threat exchanges using machine learning algorithms to ensure privacy and cybersecurity in the USA
inferred← citeshttps://doi.org/10.2478/raft-2024-0010openalex-snapshot
Codesentry: Revolutionizing Real-Time Software Vulnerability Detection With Optimized GPT Framework
inferred← citeshttps://doi.org/10.26735/zwhy8666openalex-snapshot
A Bagged Multi-Layer Perceptron Framework for Robust Phishing Website Detection
inferred← citeshttps://doi.org/10.29121/shodhkosh.v5.i3.2024.2713openalex-snapshot
WEB SPOOFING DEFENSE EMPOWERING USERS WITH PHISHCATCHER'S MACHINE LEARNING
inferred← citeshttps://doi.org/10.3103/s0146411626700021openalex-snapshot
Hybrid Machine Learning Approach for Phishing URL Detection
inferred← citeshttps://doi.org/10.31033/abjar/5.3.2026.120openalex-snapshot
An Explainable Lightweight Phishing Website Detection Framework Using Consensus Feature Selection and Performance-Weighted Ensemble Learning
inferred← citeshttps://doi.org/10.31185/wjps.143openalex-snapshot
A Critical Review: Revisiting Phishing Attacks Classification and Analysis of Techniques Employed in Taxonomies
inferred← citeshttps://doi.org/10.32604/cmc.2023.036422openalex-snapshot
Machine Learning Techniques for Detecting Phishing URL Attacks
inferred← citeshttps://doi.org/10.3389/fcomp.2024.1428013openalex-snapshot
Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning
inferred← citeshttps://doi.org/10.3389/fcomp.2026.1821417openalex-snapshot
Machine learning-based malicious URL detection using feature selection techniques and WHOIS features
inferred← citeshttps://doi.org/10.3389/frcmn.2025.1587654openalex-snapshot
Multimodal framework for phishing attack detection and mitigation through behavior analysis using EM-BERT and SPCA-BASED EAI-SC-LSTM
inferred← citeshttps://doi.org/10.3390/app14020919openalex-snapshot
Experimental Evaluation of Possible Feature Combinations for the Detection of Fraudulent Online Shops
inferred← citeshttps://doi.org/10.3390/app16178737openalex-snapshot
Adversarial Robustness in URL-Based Phishing Detection: Problem-Space Evaluation and Robust Feature Engineering
inferred← citeshttps://doi.org/10.3390/electronics10222851openalex-snapshot
A Survey of Machine Learning Techniques for Video Quality Prediction from Quality of Delivery Metrics
inferred← citeshttps://doi.org/10.3390/electronics12071642openalex-snapshot
Analysis of the Performance Impact of Fine-Tuned Machine Learning Model for Phishing URL Detection
inferred← citeshttps://doi.org/10.3390/electronics12132823openalex-snapshot
Hybrid Phishing Detection Based on Automated Feature Selection Using the Chaotic Dragonfly Algorithm
inferred← citeshttps://doi.org/10.3390/electronics13193823openalex-snapshot
A Systematic Review of Deep Learning Techniques for Phishing Email Detection
inferred← citeshttps://doi.org/10.3390/electronics13244877openalex-snapshot
Comparative Investigation of Traditional Machine-Learning Models and Transformer Models for Phishing Email Detection
inferred← citeshttps://doi.org/10.3390/electronics15112490openalex-snapshot
DYNAMIT: K-Medoids-Based Machine Learning for Scalable Honeynet Deception and Intelligent Threat Profiling
inferred← citeshttps://doi.org/10.3390/engproc2025107108openalex-snapshot
Real-Time Phishing URL Detection Using Machine Learning
inferred← citeshttps://doi.org/10.3390/fi18010030openalex-snapshot
Synergistic Phishing Intrusion Detection: Integrating Behavioral and Structural Indicators with Hybrid Ensembles and XAI Validation
inferred← citeshttps://doi.org/10.3390/make6010018openalex-snapshot
Prompt Engineering or Fine-Tuning? A Case Study on Phishing Detection with Large Language Models
inferred← citeshttps://doi.org/10.3390/math10224173openalex-snapshot
Application of Natural Language Processing and Machine Learning Boosted with Swarm Intelligence for Spam Email Filtering
inferred← citeshttps://doi.org/10.3390/math11143217openalex-snapshot
Attention-Based 1D CNN-BiLSTM Hybrid Model Enhanced with FastText Word Embedding for Korean Voice Phishing Detection
inferred← citeshttps://doi.org/10.3390/s22062194openalex-snapshot
Leveraging Computational Intelligence Techniques for Defensive Deception: A Review, Recent Advances, Open Problems and Future Directions
inferred← citeshttps://doi.org/10.3390/s23020651openalex-snapshot
A Machine Learning Approach for the NLP-Based Analysis of Cyber Threats and Vulnerabilities of the Healthcare Ecosystem
inferred← citeshttps://doi.org/10.3390/sym15020395openalex-snapshot
Contextual Embeddings-Based Web Page Categorization Using the Fine-Tune BERT Model
inferred← citeshttps://doi.org/10.3390/w15193473openalex-snapshot
Groundwater Level Prediction with Machine Learning to Support Sustainable Irrigation in Water Scarcity Regions
inferred← citeshttps://doi.org/10.34288/jri.v8i3.549openalex-snapshot
CLIENT-SIDE ONLINE GAMBLING DETECTION USING MULTI-LAYER CASCADE PATTERN MATCHING IN MANIFEST V3 CHROME EXTENSIONS
inferred← citeshttps://doi.org/10.35377/saucis...1839585openalex-snapshot
PhishShield: Early Detection of Malicious Websites via Domain Sequence Modeling and Feature-Based Classification
inferred← citeshttps://doi.org/10.35940/ijitee.c9452.0212323openalex-snapshot
Thwart and Safeguard of Cyber Crime & Cyber Attack in Computer Networks
inferred← citeshttps://doi.org/10.37275/nasetjournal.v5i1.65openalex-snapshot
Enhancing Phishing Detection in Sulu, Philippines: A Machine Learning Approach to Combat Evolving Cyber Threats
inferred← citeshttps://doi.org/10.37394/232018.2025.13.51openalex-snapshot
A Survey on URL Phishing Attacks Detection using Deep Learning Models
inferred← citeshttps://doi.org/10.37502/ijsmr.2024.7403openalex-snapshot
Phishing Detection Using Machine Learning: A Model Development and Integration
inferred← citeshttps://doi.org/10.3844/jcssp.2023.20.56openalex-snapshot
Cyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A Survey
inferred← citeshttps://doi.org/10.4018/979-8-3373-1514-0.ch006openalex-snapshot
AI-Enhanced Medical Devices for Smarter Healthcare
inferred← citeshttps://doi.org/10.4018/979-8-3373-7082-8.ch009openalex-snapshot
Multimodal Phishing Detection via Image-Text Fusion and CLIP-Based Deep Learning
inferred← citeshttps://doi.org/10.4018/ijdwm.411870openalex-snapshot
Data Mining-Driven Detection of Banking URL Phishing Using Hybrid CNN and Machine Learning Models
inferred← citeshttps://doi.org/10.4108/eetsis.4421openalex-snapshot
Combining Lexical, Host, and Content-based features for Phishing Websites detection using Machine Learning Models
inferred← citeshttps://doi.org/10.48084/etasr.11548openalex-snapshot
A Hybrid Heuristic-Machine Learning Framework for Phishing Detection Using Multi-Domain Feature Analysis
inferred← citeshttps://doi.org/10.48175/ijarsct-5043openalex-snapshot
URL’S Phishing Detection Based on Machine Learning Approach
inferred← citeshttps://doi.org/10.5121/ijcnc.2023.15102openalex-snapshot
Phishing URL Detection using LSTM Based Ensemble Learning Approaches
inferred← citeshttps://doi.org/10.52783/jes.2923openalex-snapshot
Novel Optimization-Driven Feature Selection Approach for Enhancing Phishing Website Detection Accuracy
inferred← citeshttps://doi.org/10.55057/ijares.2024.6.1.11openalex-snapshot
Hybrid Learning Challenges and Opportunities: Literature Review in Chengdu's Universities, China
inferred← citeshttps://doi.org/10.5815/ijwmt.2025.03.03openalex-snapshot
Detection and Prevention of Phishing Short URLs Using Machine Learning and Blacklist Approaches
inferred← citeshttps://doi.org/10.7717/peerj-cs.4074openalex-snapshot
Robust phishing URL detection using FastText embeddings and deep sequential models
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.