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Detecting malicious URLs using machine learning techniques: review and research directions
In recent years, the digital world has advanced significantly, particularly on the Internet,
which is critical given that many of our activities are now conducted online. As a result of …
which is critical given that many of our activities are now conducted online. As a result of …
An assessment of lexical, network, and content‐based features for detecting malicious URLs using machine learning and deep learning models
The World Wide Web services are essential in our daily lives and are available to
communities through Uniform Resource Locator (URL). Attackers utilize such means of …
communities through Uniform Resource Locator (URL). Attackers utilize such means of …
Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning
Introduction The dynamic and sophisticated nature of phishing attacks, coupled with the
relatively weak anti-phishing tools, has made phishing detection a pressing challenge. In …
relatively weak anti-phishing tools, has made phishing detection a pressing challenge. In …
PMANet: Malicious URL detection via post-trained language model guided multi-level feature attention network
The expansion of the Internet has led to the widespread proliferation of malicious URLs,
becoming a primary vector for cyber threats. Detecting malicious URLs is now essential for …
becoming a primary vector for cyber threats. Detecting malicious URLs is now essential for …
Phishing URLs detection using sequential and parallel ML techniques: comparative analysis
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) …
daily life and are accessible to the users via uniform resource locators (URLs) …
[HTML][HTML] Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model
Web applications' popularity has raised attention in various service domains, which
increased the concern about cyber-attacks. One of these most serious and frequent web …
increased the concern about cyber-attacks. One of these most serious and frequent web …
TransURL: Improving malicious URL detection with multi-layer Transformer encoding and multi-scale pyramid features
While machine learning progress is advancing the detection of malicious URLs, advanced
Transformers applied to URLs face difficulties in extracting local information, character-level …
Transformers applied to URLs face difficulties in extracting local information, character-level …
[HTML][HTML] Investigating the influence of feature sources for malicious website detection
Malicious websites in general, and phishing websites in particular, attempt to mimic
legitimate websites in order to trick users into trusting them. These websites, often a primary …
legitimate websites in order to trick users into trusting them. These websites, often a primary …
Malicious url detection via pretrained language model guided multi-level feature attention network
The widespread use of the Internet has revolutionized information retrieval methods.
However, this transformation has also given rise to a significant cybersecurity challenge: the …
However, this transformation has also given rise to a significant cybersecurity challenge: the …
Explainable Machine Learning for Bag of Words-Based Phishing Detection
Phishing is a fraudulent practice aimed at convincing individuals to reveal sensitive
information, such as account credentials or credit card details, by clicking the links of …
information, such as account credentials or credit card details, by clicking the links of …