Overview on intrusion detection systems design exploiting machine learning for networking cybersecurity

P Dini, A Elhanashi, A Begni, S Saponara, Q Zheng… - Applied Sciences, 2023 - mdpi.com
The Intrusion Detection System (IDS) is an effective tool utilized in cybersecurity systems to
detect and identify intrusion attacks. With the increasing volume of data generation, the …

Machine learning-based social media bot detection: a comprehensive literature review

M Aljabri, R Zagrouba, A Shaahid, F Alnasser… - Social Network Analysis …, 2023 - Springer
In today's digitalized era, Online Social Networking platforms are growing to be a vital aspect
of each individual's daily life. The availability of the vast amount of information and their …

Phishing URLs detection using sequential and parallel ML techniques: comparative analysis

N Nagy, M Aljabri, A Shaahid, AA Ahmed, F Alnasser… - Sensors, 2023 - mdpi.com
In today's digitalized era, the world wide web services are a vital aspect of each individual's
daily life and are accessible to the users via uniform resource locators (URLs) …

AI-based techniques for Ad click fraud detection and prevention: Review and research directions

RA Alzahrani, M Aljabri - Journal of Sensor and Actuator Networks, 2022 - mdpi.com
Online advertising is a marketing approach that uses numerous online channels to target
potential customers for businesses, brands, and organizations. One of the most serious …

[HTML][HTML] Click fraud detection for online advertising using machine learning

M Aljabri, RMA Mohammad - Egyptian Informatics Journal, 2023 - Elsevier
Advertising corporations have moved their focus to online and in-App advertisements in
response to the expansion of digital technologies and social media. Online advertising …

Efficient Classification of Malicious URLs: M-BERT-A Modified BERT Variant for Enhanced Semantic Understanding

B Yu, F Tang, D Ergu, R Zeng, B Ma, F Liu - IEEE Access, 2024 - ieeexplore.ieee.org
Malicious websites present a substantial threat to the security and privacy of individuals
using the internet. Traditional approaches for identifying these malicious sites have …

Machine learning-based detection for unauthorized access to IoT devices

M Aljabri, AA Alahmadi, RMA Mohammad… - Journal of Sensor and …, 2023 - mdpi.com
The Internet of Things (IoT) has become widely adopted in businesses, organizations, and
daily lives. They are usually characterized by transferring and processing sensitive data …

Detecting command injection attacks in web applications based on novel deep learning methods

X Wang, J Zhai, H Yang - Scientific Reports, 2024 - nature.com
Web command injection attacks pose significant security threats to web applications, leading
to potential server information leakage or severe server disruption. Traditional detection …

Improving Cybersecurity: A Comparative Analysis of Machine Learning-Based Uniform Resource Locator (URL) Classification

RG de Luna, KAR Girang, JELD Lucido… - … on Informatics and …, 2024 - ieeexplore.ieee.org
Threats on the internet are a major issue, as cyberattacks continue to pose a security
challenge due to the increasing number of malicious sites. Therefore, it is crucial to maintain …

Advances in artificial intelligence for detecting algorithmically generated domains: Current trends and future prospects

H Alqahtani, G Kumar - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
This comprehensive review navigates the complex domain of Domain Generation
Algorithms (DGAs) and their detection using Artificial Intelligence (AI), revealing both …