eHealth Library Ireland Search Results

Abstract With the rapid development of the internet, phishing attacks have become more diverse, making phishing website detection a key focus in cybersecurity. While machine learning and deep learning have led to various phishing URL detection methods, many remain incomplete, limiting accuracy. This paper proposes CSPPC-BiLSTM, a malicious URL detection model based on BiLSTM (Bidirectional Long Short-Term Memory, BiLSTM). The model processes URL character...

In the field of network econometric data analysis, the analysis of massive URL data offers insights into the behavior of networks, the optimization of network structure, and the prevention of network attacks. Therefore, this study introduces Python web scraping technology to achieve data collection in the design of econometric data analysis software, and designs a hash split Bloom filter algorithm based on multiple eigenvalues to achieve de-duplication....

Abstract Cybercriminals create phishing websites that mimic legitimate websites to get sensitive information from companies, individuals, or governments. Therefore, using state-of-the-art artificial intelligence and machine learning technologies to correctly classify phishing and legitimate URLs is imperative. We report the results of applying deterministic and probabilistic neural network models to URL classification. Key achievements of this work...

Phishing attacks continue to pose a major challenge in today’s digital world; thus, sophisticated detection techniques are required to address constantly changing tactics. In this paper, we have proposed an innovative method to identify phishing attempts using the extensive PhiUSIIL dataset. The proposed dataset comprises 134,850 legitimate URLs and 100,945 phishing URLs, providing a robust foundation for analysis. We applied the t-SNE technique...

Phishing websites, mimicking legitimate counterparts, pose significant threats by stealing user information through deceptive Uniform Resource Locators (URLs). Traditional blacklists struggle to identify dynamic URLs, necessitating advanced detection mechanisms. In this study, we propose an effective approach utilizing residual pipelining for phishing URL detection. Our method extracts common URL features and sentiments, employing a residual pipeline...

The uniform resource locator (URL) conveys essential information about a page’s topic, authority, and security, which significantly influences its ranking in search engine results. However, many existing URL classification methods used for real-time online inference face challenges related to time and memory complexity during preprocessing, processing, and inference stages. In environments where quick decision-making is crucial, such as cybersecurity...

Phishing attempts to mimic the official websites of businesses, including banks, e-commerce, government offices, and financial institutions. Phishing websites aim to collect and retrieve sensitive data from users, including passwords, credit card numbers, email addresses, personal information, and so on. The growing frequency of phishing attacks has prompted the development of numerous anti-phishing technologies. Because machine learning (ML) techniques...

ABSTRACTIn recent decades, Digital transformation has significantly shifted human activities from physical space to cyber space. When users access the internet, uniform resource locator (URL) data are autogenerated. Using URLs, this study presents a novel framework for exploring cyber space structure from the perspectives of complex networks and activity fragmentation. Web domains within URL data are metaphorically regarded as ‘digital locations,’...

Currently, numerous types of cybercrime are organized through the internet. Hence, this study mainly focuses on phishing attacks. Although phishing was first used in 1996, it has become the most severe and dangerous cybercrime on the internet. Phishing utilizes email distortion as its underlying mechanism for tricky correspondences, followed by mock sites, to obtain the required data from people in question. Different studies have presented their...