GramBeddings: a new neural network for URL based identification of phishing web pages through n-gram embeddings

AS Bozkir, FC Dalgic, M Aydos - Computers & Security, 2023 - Elsevier
There has been ever-growing use of Internet and progress within many communication
channels such as social media and this escalates the need for rapid and low source …

Phishing URL detection via CNN and attention-based hierarchical RNN

Y Huang, Q Yang, J Qin, W Wen - 2019 18th IEEE International …, 2019 - ieeexplore.ieee.org
Phishing websites have long been a serious threat to cyber security. For decades, many
researchers have been devoted to developing novel techniques to detect phishing websites …

Dynamic recognition of phishing URLs using deep learning techniques

S Sountharrajan, M Nivashini, SK Shandilya… - Advances in cyber …, 2020 - Springer
Phishing is a critical issue that faces the digital security. The straightforwardness of the web
and Internet uncovered open doors for offenders to transfer malevolent substance at the …

Texception: a character/word-level deep learning model for phishing URL detection

F Tajaddodianfar, JW Stokes… - ICASSP 2020-2020 …, 2020 - ieeexplore.ieee.org
Phishing is the starting point for many cyberattacks that threaten the confidentiality,
availability and integrity of enterprises' and consumers' data. The URL of a web page that …

Optimized URL feature selection based on genetic-algorithm-embedded deep learning for phishing website detection

SJ Bu, HJ Kim - Electronics, 2022 - mdpi.com
Deep learning models for phishing URL classification based on character-and word-level
URL features achieve the best performance in terms of accuracy. Various improvements …

TCURL: Exploring hybrid transformer and convolutional neural network on phishing URL detection

C Wang, Y Chen - Knowledge-Based Systems, 2022 - Elsevier
Phishing is a growing threat that involves cybercriminals creating counterfeit websites to lure
victims and obtain their sensitive information, such as login credentials and credit card …

An effective phishing detection model based on character level convolutional neural network from URL

A Aljofey, Q Jiang, Q Qu, M Huang, JP Niyigena - Electronics, 2020 - mdpi.com
Phishing is the easiest way to use cybercrime with the aim of enticing people to give
accurate information such as account IDs, bank details, and passwords. This type of …

[PDF][PDF] Robust URL Phishing Detection Based on Deep Learning.

A Al-Alyan, S Al-Ahmadi - KSII Transactions on Internet & Information …, 2020 - itiis.org
Phishing websites can have devastating effects on governmental, financial, and social
services, as well as on individual privacy. Currently, many phishing detection solutions are …

CNN–MHSA: A Convolutional Neural Network and multi-head self-attention combined approach for detecting phishing websites

X Xiao, D Zhang, G Hu, Y Jiang, S Xia - Neural Networks, 2020 - Elsevier
Increasing phishing sites today have posed great threats due to their terribly imperceptible
hazard. They expect users to mistake them as legitimate ones so as to steal user information …

A large-scale pretrained deep model for phishing url detection

Y Wang, W Zhu, H Xu, Z Qin, K Ren… - ICASSP 2023-2023 …, 2023 - ieeexplore.ieee.org
Phishing attacks have always been a security issue that has attracted great attention in the
cyber security community. Recently, the famous pre-trained models is being used as an anti …