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PhishFusion: Domain-Adaptive Contrastive Representation Learning and Multi-Source Fusion under Distribution Shift in Phishing URL Detection

https://doi.org/10.2139/ssrn.6880638
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inferredcites →https://doi.org/10.1007/978-3-319-46298-1_30openalex-snapshot
Detecting Malicious URLs Using Lexical Analysis
inferredcites →https://doi.org/10.1007/s10922-025-10010-9openalex-snapshot
DomURLs_BERT: Pre-trained BERT-based Model for Malicious Domains and URLs Detection and Classification
inferredcites →https://doi.org/10.1007/s11235-017-0414-0openalex-snapshot
Towards detection of phishing websites on client-side using machine learning based approach
inferredcites →https://doi.org/10.1007/s12652-019-01311-4openalex-snapshot
CatchPhish: detection of phishing websites by inspecting URLs
inferredcites →https://doi.org/10.1007/s13042-025-02968-4openalex-snapshot
Mutual impact of feature selection and privacy-preserving mechanisms
inferredcites →https://doi.org/10.1016/j.cose.2021.102584openalex-snapshot
HDP-CNN: Highway deep pyramid convolution neural network combining word-level and character-level representations for phishing website detection
inferredcites →https://doi.org/10.1016/j.cose.2022.102964openalex-snapshot
GramBeddings: A New Neural Network for URL Based Identification of Phishing Web Pages Through N-gram Embeddings
inferredcites →https://doi.org/10.1016/j.eswa.2018.09.029openalex-snapshot
Machine learning based phishing detection from URLs
inferredcites →https://doi.org/10.1016/j.ins.2023.02.039openalex-snapshot
CNN-Fusion: An effective and lightweight phishing detection method based on multi-variant ConvNet
inferredcites →https://doi.org/10.1016/j.knosys.2022.109955openalex-snapshot
TCURL: Exploring hybrid transformer and convolutional neural network on phishing URL detection
inferredcites →https://doi.org/10.1038/s42256-020-00257-zopenalex-snapshot
Shortcut learning in deep neural networks
inferredcites →https://doi.org/10.1109/access.2022.3151903openalex-snapshot
Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions
inferredcites →https://doi.org/10.1109/access.2022.3168681openalex-snapshot
Phishing URL Detection: A Real-Case Scenario Through Login URLs
inferredcites →https://doi.org/10.1109/access.2023.3268027openalex-snapshot
PhiKitA: Phishing Kit Attacks Dataset for Phishing Websites Identification
inferredcites →https://doi.org/10.1109/access.2024.3352629openalex-snapshot
DEPHIDES: Deep Learning Based Phishing Detection System
inferredcites →https://doi.org/10.1109/milcom52596.2021.9653028openalex-snapshot
URLTran: Improving Phishing URL Detection Using Transformers
inferredcites →https://doi.org/10.1109/tbdata.2019.2921572openalex-snapshot
Billion-Scale Similarity Search with GPUs
inferredcites →https://doi.org/10.1109/tdsc.2025.3545771openalex-snapshot
BERT-PhishFinder: A Robust Model for Accurate Phishing URL Detection With Optimized DistilBERT
inferredcites →https://doi.org/10.1109/tnsm.2014.2377295openalex-snapshot
PhishStorm: Detecting Phishing With Streaming Analytics
inferredcites →https://doi.org/10.18637/jss.v036.i11openalex-snapshot
Feature Selection with the Boruta Package
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