[HTML][HTML] A Decision-Fusion-Based Ensemble Approach for Malicious Websites Detection

A Alanazi, A Gumaei - Applied Sciences, 2023 - mdpi.com
Malicious websites detection is one of the cyber-security tasks that protects sensitive
information such as credit card details and login credentials from attackers. Machine …

[HTML][HTML] Significance of machine learning for detection of malicious websites on an unbalanced dataset

I Ul Hassan, RH Ali, Z Ul Abideen, TA Khan, R Kouatly - Digital, 2022 - mdpi.com
It is hard to trust any data entry on online websites as some websites may be malicious, and
gather data for illegal or unintended use. For example, bank login and credit card …

Detection of malicious websites using machine learning techniques

A Oshingbesan, C Ekoh, C Okobi, A Munezero… - arXiv preprint arXiv …, 2022 - arxiv.org
In detecting malicious websites, a common approach is the use of blacklists which are not
exhaustive in themselves and are unable to generalize to new malicious sites. Detecting …

Malweb: An efficient malicious websites detection system using machine learning algorithms

AE El-Din, EED Hemdan… - … Conference on Electronic …, 2021 - ieeexplore.ieee.org
These days, malware is one of the supreme acknowledged cyber threats. As data volumes
increase rapidly, the number of malware threats increases. Malware not only increases in …

[HTML][HTML] Safeguarding cyberspace: Enhancing malicious website detection with PSOoptimized XGBoost and firefly-based feature selection

S Sheikhi, P Kostakos - Computers & Security, 2024 - Elsevier
In recent years, the exponential growth of internet usage worldwide has created a conducive
environment for the expansion of malicious activities. Among these threats, malicious …

A Review of Data-Driven Approaches for Malicious Website Detection

Z Hu, Z Yuan - 2023 7th Asian Conference on Artificial …, 2023 - ieeexplore.ieee.org
The detection of malicious websites has become a critical issue in cybersecurity. Therefore,
this paper offers a comprehensive review of data-driven methods for detecting malicious …

A comparison of machine learning attributes for detecting malicious websites

AK Singh, N Goyal - 2019 11th International Conference on …, 2019 - ieeexplore.ieee.org
The number of Malicious Websites has increased manifold in the past few years. As on start
of year 2018, 1 in every 13 URL was malicious, amounting to 7.8% URLs identified as …

A HYBRID APPROACH FOR DETECTING MALICIOUS WEB PAGES USING DECISION TREE AND NAÏVE BAYES ALGORITHMS.

SA Onashoga, A Abayomi-Alli… - Computer Science & …, 2016 - search.ebscohost.com
Recent advances in computers and computer networks have made webpages a potential
target for malicious activities by hackers. In this study, a hybrid malicious URL detection …

[HTML][HTML] A heterogeneous machine learning ensemble framework for malicious webpage detection

SS Shin, SG Ji, SS Hong - Applied Sciences, 2022 - mdpi.com
The growing dependence on digital systems has heightened the risks posed by
cybersecurity threats. This paper proposes a new method for detecting malicious webpages …

[PDF][PDF] A Machine learning approach to improve the efficiency of Fake websites detection Techniques

A Dakwala, K Lavingia - International journal of computer Science …, 2016 - csjournals.com
Phishing is a kind of cyber-attack in which perpetrators use spoofed emails and fallacious
web sites to lure unsuspecting online users into giving up personal data. This paper takes a …