[HTML][HTML] The applicability of a hybrid framework for automated phishing detection

RJ van Geest, G Cascavilla, J Hulstijn, N Zannone - Computers & Security, 2024 - Elsevier
Phishing attacks are a critical and escalating cybersecurity threat in the modern digital
landscape. As cybercriminals continually adapt their techniques, automated phishing …

PDHF: Effective phishing detection model combining optimal artificial and automatic deep features

E Zhu, K Cheng, Z Zhang, H Wang - Computers & Security, 2024 - Elsevier
Currently, the increasing number of high-volume phishing attacks is among the largest
threats to networking environments on a daily basis. During such a severe attack …

An in-depth benchmarking and evaluation of phishing detection research for security needs

A El Aassal, S Baki, A Das, RM Verma - Ieee Access, 2020 - ieeexplore.ieee.org
We perform an in-depth, systematic benchmarking study and evaluation of phishing features
on diverse and extensive datasets. We propose a new taxonomy of features based on the …

Deep learning for phishing detection: Taxonomy, current challenges and future directions

NQ Do, A Selamat, O Krejcar, E Herrera-Viedma… - Ieee …, 2022 - ieeexplore.ieee.org
Phishing has become an increasing concern and captured the attention of end-users as well
as security experts. Existing phishing detection techniques still suffer from the deficiency in …

AI-Based Phishing Detection Techniques: A Comparative Analysis of Model Performance

BR Maddireddy, BR Maddireddy - Unique Endeavor in Business & Social …, 2022 - unbss.com
Phishing attacks continue to pose significant threats to cybersecurity, targeting individuals,
businesses, and organizations worldwide. In response, researchers and practitioners have …

Enhancing phishing detection: A novel hybrid deep learning framework for cybercrime forensics

FS Alsubaei, AA Almazroi, N Ayub - IEEE Access, 2024 - ieeexplore.ieee.org
Protecting against interference is essential at a time when wireless communications are
essential for sending large amounts of data. Our research presents a novel deep learning …

[HTML][HTML] Towards a multi-layered phishing detection

K Rendall, A Nisioti, A Mylonas - Sensors, 2020 - mdpi.com
Phishing is one of the most common threats that users face while browsing the web. In the
current threat landscape, a targeted phishing attack (ie, spear phishing) often constitutes the …

A methodical overview on phishing detection along with an organized way to construct an anti-phishing framework

S Patil, S Dhage - 2019 5th International Conference on …, 2019 - ieeexplore.ieee.org
Phishing is a security attack to acquire personal information like passwords, credit card
details or other account details of a user by means of websites or emails. Phishing websites …

Phishing attacks detection a machine learning-based approach

F Salahdine, Z El Mrabet… - 2021 IEEE 12th Annual …, 2021 - ieeexplore.ieee.org
Phishing attacks are one of the most common social engineering attacks targeting users'
emails to fraudulently steal confidential and sensitive information. They can be used as a …

[PDF][PDF] Building robust phishing detection system: an empirical analysis

J Lee, P Ye, R Liu, DM Divakaran, MC Chan - NDSS MADWeb, 2020 - researchgate.net
To tackle phishing attacks, recent research works have resorted to the application of
machine learning (ML) algorithms, yielding promising results. Often, a binary classification …