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 …

SoK: a comprehensive reexamination of phishing research from the security perspective

A Das, S Baki, A El Aassal, R Verma… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
Phishing and spear phishing are typical examples of masquerade attacks since trust is built
up through impersonation for the attack to succeed. Given the prevalence of these attacks …

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 …

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 detection: a literature survey

M Khonji, Y Iraqi, A Jones - IEEE Communications Surveys & …, 2013 - ieeexplore.ieee.org
This article surveys the literature on the detection of phishing attacks. Phishing attacks target
vulnerabilities that exist in systems due to the human factor. Many cyber attacks are spread …

A new hybrid ensemble feature selection framework for machine learning-based phishing detection system

KL Chiew, CL Tan, KS Wong, KSC Yong, WK Tiong - Information Sciences, 2019 - Elsevier
This paper proposes a new feature selection framework for machine learning-based
phishing detection system, called the Hybrid Ensemble Feature Selection (HEFS). In the first …

A comprehensive survey of AI-enabled phishing attacks detection techniques

A Basit, M Zafar, X Liu, AR Javed, Z Jalil… - Telecommunication …, 2021 - Springer
In recent times, a phishing attack has become one of the most prominent attacks faced by
internet users, governments, and service-providing organizations. In a phishing attack, the …

Phishing attacks detection using machine learning and deep learning models

M Aljabri, S Mirza - 2022 7th International Conference on Data …, 2022 - ieeexplore.ieee.org
Because of the fast expansion of internet users, phishing attacks have become a significant
menace where the attacker poses as a trusted entity in order to steal sensitive data, causing …

Learning from the ones that got away: Detecting new forms of phishing attacks

CN Gutierrez, T Kim, R Della Corte… - … on Dependable and …, 2018 - ieeexplore.ieee.org
Phishing attacks continue to pose a major threat for computer system defenders, often
forming the first step in a multi-stage attack. There have been great strides made in phishing …

Systematization of knowledge (sok): A systematic review of software-based web phishing detection

Z Dou, I Khalil, A Khreishah… - … Surveys & Tutorials, 2017 - ieeexplore.ieee.org
Phishing is a form of cyber attack that leverages social engineering approaches and other
sophisticated techniques to harvest personal information from users of websites. The …