A hybrid framework using explainable AI (XAI) in cyber-risk management for defence and recovery against phishing attacks

B Biswas, A Mukhopadhyay, A Kumar… - Decision Support Systems, 2024 - Elsevier
Phishing and social engineering contribute to various cyber incidents such as data breaches
and ransomware attacks, financial frauds, and denial of service attacks. Often, phishers …

CNN-Fusion: An effective and lightweight phishing detection method based on multi-variant ConvNet

M Hussain, C Cheng, R Xu, M Afzal - Information Sciences, 2023 - Elsevier
Phishing scams are increasing as the technical skills and costs of phishing attacks diminish,
emphasizing the need for rapid, precise, and low-cost prevention measures. Based on a …

BERT-Based Approaches to Identifying Malicious URLs

MY Su, KL Su - Sensors, 2023 - mdpi.com
Malicious uniform resource locators (URLs) are prevalent in cyberattacks, particularly in
phishing attempts aimed at stealing sensitive information or distributing malware. Therefore …

Machine Learning-Based Phishing Detection Using URL Features: A Comprehensive Review

AUZ Asif, H Shirazi, I Ray - … Symposium on Stabilizing, Safety, and Security …, 2023 - Springer
Phishing is a social engineering attack in which an attacker sends a fraudulent message to a
user in the hope of obtaining sensitive confidential information. Machine learning appears to …

An Ontology-Based Cybersecurity Framework for AI-Enabled Systems and Applications

D Preuveneers, W Joosen - Future Internet, 2024 - mdpi.com
Ontologies have the potential to play an important role in the cybersecurity landscape as
they are able to provide a structured and standardized way to semantically represent and …

PhishHunter: Detecting camouflaged IDN-based phishing attacks via Siamese neural network

M Wang, X Zang, J Cao, B Zhang, S Li - Computers & Security, 2024 - Elsevier
Phishing is one of the significant threats to cybersecurity today, especially when attackers
create Internationalized Domain Names (IDN) homographs to engage in phishing activities …

Malicious URL Detection via Pretrained Language Model Guided Multi-Level Feature Attention Network

R Liu, Y Wang, H Xu, Z Qin, Y Liu, Z Cao - arXiv preprint arXiv:2311.12372, 2023 - arxiv.org
The widespread use of the Internet has revolutionized information retrieval methods.
However, this transformation has also given rise to a significant cybersecurity challenge: the …

TSTEM: A Cognitive Platform for Collecting Cyber Threat Intelligence in the Wild

P Balasubramanian, S Nazari, DK Kholgh… - arXiv preprint arXiv …, 2024 - arxiv.org
The extraction of cyber threat intelligence (CTI) from open sources is a rapidly expanding
defensive strategy that enhances the resilience of both Information Technology (IT) and …

PassREfinder: Credential Stuffing Risk Prediction by Representing Password Reuse between Websites on a Graph

J Kim, M Song, M Seo, Y Jin, S Shin - 2024 IEEE Symposium on …, 2023 - computer.org
The prevalence of credential stuffing has caused devastating harm to online users who tend
to reuse passwords across websites. In response, researchers have made efforts to detect …

A cyber defense system against phishing attacks with deep learning game theory and LSTM-CNN with African vulture optimization algorithm (AVOA)

MA Elberri, Ü Tokeşer, J Rahebi… - International Journal of …, 2024 - Springer
Phishing attacks pose a significant threat to online security, utilizing fake websites to steal
sensitive user information. Deep learning techniques, particularly convolutional neural …