In today’s world, electronics and networked systems, such as IoT devices, embedded platforms and smart environments, are increasingly popular and widespread. As a result, these systems become more exposed to cyber threats. The malicious URL is...
Due to the indispensable use of the internet, malicious actors have exploited URLs as a threat source of network information security and integrity. URL detection based on traditional methods has become inefficient against the uncontrolled increase o...
Cybercriminals use malicious URLs as distribution channels to propagate malware over the web. Attackers exploit vulnerabilities in browsers to install malware to have access to the victim’s computer remotely. The purpose of most malware is to gain ac...
The increasing reliance on Internet-based services has been accompanied by a rapid growth in cyber threats, particularly phishing attacks using misleading Uniform Resource Locators (URLs) to mislead users and compromise sensitive data. This paper pro...
Nowadays, the majority of everyday computing devices, irrespective of their size and operating system, allow access to information and online services through web browsers. However, the pervasiveness of web browsing in our daily life does not come wi...
Large language models are increasingly embedded in e-commerce assistants that recommend links to shopping destinations. When the candidate set contains adversarially crafted phishing URLs, a fluent model can recommend a malicious link with the same c...
With the rapid development of Internet technology, numerous malicious URLs have appeared, which bring a large number of security risks. Efficient detection of malicious URLs has become one of the keys for defense against cyber attacks. Deep learning...
Generative Pre-Trained Transformer (GPT) models excel in text generation, text compilation, and language-related tasks. ChatGPT is based on the GPT model that responds to queries and has human-like conversational capabilities. This includes writing p...
With the enhancement of the Internet of Things (IoT), smart cities have developed the idea of conventional urbanization. IoT networks permit distributed smart devices to collect and process data in smart city structures utilizing an open channel, the...
The rapid growth of web-based services has intensified the need for reliable mechanisms to distinguish malicious Uniform Resource Locators (URLs) from legitimate ones. Phishing campaigns, malware distribution networks, and defacement operations incre...
In today’s world, phishing attacks are gradually increasing, resulting in individuals losing valuables, assets, personal information, etc., to unauthorized parties. In phishing, attackers craft malicious websites disguised as well-known, legiti...
The constant rise of malicious URLs continues to pose significant threats and challenges in cybersecurity, with attackers increasingly evading classical detection methods like blacklists and heuristic-based systems. While machine learning (ML) techni...
Recently, phishing attacks have been a crucial threat to cyberspace security. Phishing is a form of fraud that attracts people and businesses to access malicious uniform resource locators (URLs) and submit their sensitive information such as password...
The study investigates the use of powerful machine learning approaches to the real-time detection of phishing URLs, addressing a critical cybersecurity concern. The dataset we utilized in this research work was collected from the University of Califo...
Phishing is the easiest way to use cybercrime with the aim of enticing people to give accurate information such as account IDs, bank details, and passwords. This type of cyberattack is usually triggered by emails, instant messages, or phone calls. Th...
Deep learning models for phishing URL classification based on character- and word-level URL features achieve the best performance in terms of accuracy. Various improvements have been proposed through deep learning parameters, including the structure...
Infected URLs are always regarded as a serious threat to cybersecurity, serving as pathways to phishing, maliciousness, and other offenses. Although transformer-based models have demonstrated good performance in malicious URL detection, their high co...
Web applications have become ubiquitous for many business sectors due to their platform independence and low operation cost. Billions of users are visiting these applications to accomplish their daily tasks. However, many of these applications are ei...
Phishing and malicious websites are a serious threat on the internet. Attackers use fake links to trick users and steal their private information. Detecting these links is difficult because attackers change their tricks often. Many old methods cannot...
Phishing sites are increasingly causing harm to consumers, commercial enterprises, and the online infrastructure. Online safety is dependent on how well these evil sites can be detected in time and correctly. A number of solutions that exist are base...
Phishing, especially brand impersonation attacks, is a critical cybersecurity threat that harms user trust and organization security. This paper establishes a lightweight model for real-time detection that relies on URL-only sequences, addressing lim...
With the rapid development of the Internet, malicious URL detection has emerged as a critical challenge in the field of cyberspace security. Traditional machine-learning techniques and subsequent deep-learning frameworks have shown limitations in han...
The escalating reliance on revolutionary online web services has introduced heightened security risks, with persistent challenges posed by phishing despite extensive security measures. Traditional phishing systems, reliant on machine learning and man...
Phishing leverages people’s tendency to share personal information online. Phishing attacks often begin with an email and can be used for a variety of purposes. The cybercriminal will employ social engineering techniques to get the target to cl...
Machine learning has become a widely adopted approach for URL-based phishing detection, with many studies reporting F1 scores exceeding 0.95 on benchmark datasets. However, recent adversarial machine learning research has questioned the robustness of...
The integration of artificial intelligence (AI) and machine learning (ML) into cybersecurity practice has increased the need for hands-on, data-driven learning in cybersecurity education. This paper presents a classroom-oriented phishing URL classifi...
Phishing attacks present a critical cybersecurity threat, with global financial losses exceeding USD 70 million in 2024. Modern machine-learning-based detection methods achieve high accuracy but have fundamental limitations, including lack of interpr...
Malicious uniform resource locators (URLs) are prevalent in cyberattacks, particularly in phishing attempts aimed at stealing sensitive information or distributing malware. Therefore, it is of paramount importance to accurately detect malicious URLs....
Researchers have proposed many models for the identification of malicious URLs in network security, but they have not achieved good results. In order to improve this defect, the current popular machine learning algorithm is combined to train the mode...
Amid the rapid proliferation of thousands of new websites daily, distinguishing safe ones from potentially harmful ones has become an increasingly complex task. These websites often collect user data, and, without adequate cybersecurity measures such...
Online social network (OSN) users are increasingly interacting with each other via articles, comments, and responses. When access control mechanisms are weak or absent, OSNs are perceived by attackers as rich environments for influencing public opini...
Malicious URLs exhibit diverse patterns and rapid evolution in complex network environments. Traditional detection methods often focus solely on local patterns or global dependencies, failing to capture multi-scale information effectively, thus limit...
The rapid growth of internet usage in daily life has led to a significant increase in cyber threats, with malicious URLs serving as a common cybercrime. Traditional detection methods often suffer from high false alarm rates and struggle to keep pace...
26 October 2024
The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate harmful conte...
In this study, we aimed to identify spatial clusters of countries with high rates of cyber attacks directed at other countries. The cyber attack dataset was obtained from Canadian Institute for Cybersecurity, with over 110,000 Uniform Resource Locato...
Phishing attacks are a major threat to online security, resulting in millions of dollars in losses. These attacks constantly evolve, forcing the cyber security community to improve detection systems. One major problem with current detection systems i...
The proliferation of algorithmically generated malicious URLs presents a critical challenge for modern cybersecurity, requiring a shift from syntactic pattern-matching toward semantic understanding grounded in pre-trained transformer foundations. Bui...
Considering the fatality of phishing attacks, the data-driven approach using massive URL observations has been verified, especially in the field of cyber security. On the other hand, the supervised learning approach relying on known attacks has limit...
The proliferation of algorithmically generated malicious URLs has overwhelmed traditional threat intelligence systems, necessitating a paradigm shift from reactive, single-instance analysis to proactive, automated campaign discovery. Existing systems...
This study presents a comprehensive comparative analysis of machine learning, deep learning, and optimization-based hybrid methods for malicious URL detection on the Malicious Phish dataset. For feature selection and model hyperparameter tuning, the...
The aim of this paper is to determine the physical proximity of connected things when they are accessed from a smartphone. Links between connected things and mobile communication devices are temporarily created by means of dynamic URLs (uniform resou...
Detecting phishing webpages is a critical task in the field of cybersecurity, with significant implications for online safety and data protection. Traditional methods have primarily relied on analyzing URL features, which can be limited in capturing...
The proliferation of online fraud has resulted in substantial financial damage to individuals and organizations alike, with web phishing emerging as one of the most pervasive and harmful attack vectors. In response, this paper proposes the Stacking E...
The proliferation of algorithmically generated malicious URLs necessitates a shift from syntactic detection to semantic analysis. This paper introduces PhishGraph, a disk-aware Approximate Nearest Neighbor (ANN) search system designed to perform bill...
The growing dependence on digital systems has heightened the risks posed by cybersecurity threats. This paper proposes a new method for detecting malicious webpages among several adversary activities. As shown in previous studies, malicious URL detec...
Phishing attacks are evolving with more sophisticated techniques, posing significant threats. Considering the potential of machine-learning-based approaches, our research presents a similar modern approach for web phishing detection by applying power...
The application of fault-slip seismic sources is critical to the success of ground motion dynamic response analysis. Previous research established a finite seismic source to analyze stability in underground engineering. In this paper, a sophisticated...
Web phishing is a form of cybercrime aimed at tricking people into visiting malicious URLs to exfiltrate sensitive data. Since the structure of a malicious URL evolves over time, phishing detection mechanisms that can adapt to such variations are par...
Phishing emails remain a significant concern and a growing cybersecurity threat in online communication. They often bypass traditional filters due to their increasing sophistication. This study presents a comparative evaluation of machine learning (M...
The crystalline rock formations of the Canadian Shield are currently one candidate rock type for the geological disposal of radioactive waste in Canada. This article starts with a critical review of past research results on the geomechanical behaviou...
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