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17 articles for “URL detection”
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Real-time Malicious URL Detection Using Machine Learning
Abstract: In malicious URLs (universal resource locators)discovery, antiquated classifiers are tested because of the information volume is enormous, designs are dynamical over the long haul, and furthermore the relationships among choices are modern. Feature engineering plays a crucial role in addressing these issues. To raised representation, the underlying the drawback and improve the performances of classifiers in characteristic malicious URLs.This paper proposes a mixture of linear and non-linear house transformation strategies. …
Published in Journal of Web Engineering & Technology · Vol. 8, Issue 1, 2021 · pp. 8–13 Read article
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Cyber Security Implementation Through Deep Learning Based Fraudulent URL Detection
Abstract: A malicious URL, sometimes known as Spam, malicious ads, and drive-by vulnerabilities may all be found on a site that is malevolent. To find rogue URLs, you need to be quick. Researchers previously used blacklisting, regular expression searching and signature matching in their investigations. These strategies are worthless for discovering new malicious URLs or updated versions of previously problematic URLs. A machine learning-based approach may be developed to overcome this …
Published in Recent Trends in Programming languages · Vol. 9, Issue 2, 2022 · pp. 35–42 Read article
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Phishing URL Detection Using Machine Learning Classification Algorithms
Abstract: Phishing attack is utilized to get the data like username, secret phrase, financial balance subtleties, and credit card details. Today, is the most well-known cybercrime. Phishing assaults additionally influence the web-based installment area monetary organization, document facilitating or distributed storage, and numerous others. Phishing assault generally focuses to these Web locales which are connected with the internet-based payment area and Web mail. To stop phishing attacks, a variety of methods …
Published in Journal of Web Engineering & Technology · Vol. 9, Issue 3, 2022 · pp. 22–33 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article
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Detecting Phishing Websites Using Hybrid Methodologies
Abstract: In the digital era, personal information theft has become a widespread and increasingly severe crime. Cybercriminals, often known as hackers, use deceptive strategies, with phishing websites being a major method for stealing confidential data. These fake websites imitate legitimate ones, tricking users into revealing sensitive personal and financial information, which has led to a rise in fraud cases. To address this escalating threat, a comprehensive research paper is proposed. This …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 59–65 Read article
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Enhancing Online Security: Machine Learning Methods for Phishing Detection—Literature Survey
Abstract: Phishing attacks represent a substantial online security threat as they mimic authentic websites to trick users into disclosing sensitive information. Detecting these malicious websites is crucial for safeguarding user data and maintaining digital trust. This summary provides insight into the application of machine learning methods in the identification of phishing websites. Machine learning, which falls under the umbrella of artificial intelligence, has proven to be a robust instrument for automating …
Published in Journal of Web Engineering & Technology · Vol. 10, Issue 3, 2023 · pp. 29–34 Read article
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Advancements in Phishing Detection: Automated Systems in Real-World Scenarios
Abstract: The goal of the abstract is to offer an automated method that uses login URLs to identify real-world scenarios. Phishing is a type of cyberattack that involves social engineering, when malefactors trick victims into providing their login credentials via a login form that sends the information to a hostile site. In this research, we offer a system that uses URL analysis to detect phishing websites by comparing machine learning and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 12–17 Read article
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Social Media Blog Analysis using Watson Analytics
Abstract: AbstractAnalytics is defined as the discovery, interpretation, and communication of meaningful patterns in data. A blog is a discussion or informational website published on the world wide web consisting of discrete, often informal diary-style text entries and may contain unstructured or semi-structured data. The analysis of unstructured data types is current challenge, getting attention in industry. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization and information privacy. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 3, 2016 · pp. 15–21 Read article
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Phishing Website Detection
Abstract: As another type of malevolent software, phishing websites show up much of the time as of late, which cause extraordinary damage to online budgetary administrations and information security. In this paper, we plan and execute an insightful model for recognizing phishing sites. In this model, we remove 10 distinct kinds of highlights, for example, title, watchword and connection text data to speak to the site. Heterogeneous classifiers are then assembled …
Published in Journal of Advances in Shell Programming · Vol. 7, Issue 2, 2020 · pp. 6–10 Read article
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Intrusion Eye Detector
Abstract: Uncertainty about security risks and illegal access are becoming more prevalent in a variety of settings, such as private homes, business buildings, and critical government buildings. Conventional security systems, which may not offer real-time warnings or prompt reactions, frequently rely on passive monitoring, including CCTV cameras and motion sensors. Artificial intelligence (AI) and computer vision-based intelligent systems are becoming more and more popular as a means of improving security and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 28–32 Read article
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Surakshit: An Android Application for Women Safety
Abstract: Every day, there are a growing number of crimes against women, including eve teasing, sexual assaults, and domestic abuse. To address the issue of personal security, we are introducing “Surakshit”, a smartphone application that provides a simple solution. With just one click, the app utilizes GPS to instantly detect the user's location, sends a message containing the location URL to registered contacts, and initiates a call to the first registered …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 10, Issue 1, 2023 · pp. 7–14 Read article
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PEGASUS: A Privacy Killer—Some Unknown Facts
Abstract: In today’s time, world is full of various new and advanced technologies. With every new technology arriving, comes new challenges which cannot be ignored. Today, almost every industry has its root penetrated deep into the internet and its applications. Therefore, internet becomes a mediator or a common platform where organizations keep and exchange their data. With the increase in cybercrimes, providing cyber security is the need of the hour. One …
Published in Journal of Web Engineering & Technology · Vol. 9, Issue 3, 2022 · pp. 8–12 Read article
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AI-Based Machine Learning Web Application Firewall (ML-WAF)
Abstract: This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security. The system analyzes diverse components of HTTP requests, including request methods, URLs, headers, cookies, and payload content, to accurately identify and classify malicious behavior. The proposed model targets a wide range of common and critical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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An Eccentric Approach For Spoofing Bother Detection
Abstract: AbstractSpoofing is a special type of network bother where the bother creates a replica of an existing web page to fool users into submitting personal, financial, or password data to what they think is their service provider’s web site. This proposed work is to find a new anti-spoofing algorithm for LGA (link guard) and DSA, which is filtering the spoofing characters in the websites of the hyperlinks in spoofing bothers. …
Published in Journal of Advances in Shell Programming · Vol. 4, Issue 2, 2017 · pp. 5–9 Read article