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 …

Anti-phishing: A comprehensive perspective

G Varshney, R Kumawat, V Varadharajan… - Expert Systems with …, 2024 - Elsevier
Phishing is a form of deception technique that attackers often use to acquire sensitive
information related to individuals and organizations fraudulently. Although Phishing attacks …

Phishing website detection with semantic features based on machine learning classifiers: a comparative study

A Almomani, M Alauthman, MT Shatnawi… - … Journal on Semantic …, 2022 - igi-global.com
The phishing attack is one of the main cybersecurity threats in web phishing and spear
phishing. Phishing websites continue to be a problem. One of the main contributions to our …

A novel approach for phishing URLs detection using lexical based machine learning in a real-time environment

BB Gupta, K Yadav, I Razzak, K Psannis… - Computer …, 2021 - Elsevier
In recent times, we can see a massive increase in the number of devices that are being
connected to the internet. These devices include but are not limited to smartphones, IoT, and …

Who are the phishers? phishing scam detection on ethereum via network embedding

J Wu, Q Yuan, D Lin, W You, W Chen… - … on Systems, Man …, 2020 - ieeexplore.ieee.org
Recently, blockchain technology has become a topic in the spotlight but also a hotbed of
various cybercrimes. Among them, phishing scams on blockchain have been found to make …

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 …

On the effectiveness of machine and deep learning for cyber security

G Apruzzese, M Colajanni, L Ferretti… - … conference on cyber …, 2018 - ieeexplore.ieee.org
Machine learning is adopted in a wide range of domains where it shows its superiority over
traditional rule-based algorithms. These methods are being integrated in cyber detection …

Malicious URL detection using machine learning: A survey

D Sahoo, C Liu, SCH Hoi - arxiv preprint arxiv:1701.07179, 2017 - arxiv.org
Malicious URL, aka malicious website, is a common and serious threat to cybersecurity.
Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure …

[PDF][PDF] Phishing scam detection on Ethereum: Towards financial security for blockchain ecosystem.

W Chen, X Guo, Z Chen, Z Zheng, Y Lu - IJCAI, 2020 - ijcai.org
In recent years, blockchain technology has created a new cryptocurrency world and has
attracted a lot of attention. It also is rampant with various scams. For example, phishing …

Phishing scams detection in ethereum transaction network

L Chen, J Peng, Y Liu, J Li, F **e, Z Zheng - ACM Transactions on …, 2020 - dl.acm.org
Blockchain has attracted an increasing amount of researches, and there are lots of
refreshing implementations in different fields. Cryptocurrency as its representative …