[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122886-en":3,"doc-seo-122886-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},122886,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Analytics of Phishing Attacks Using Machine Learning","Phishing attacks are a prevalent type of computer network attack carried out by cybercriminals to obtain sensitive information such as usernames, passwords, and banking details. The study focuses on URL phishing, where attackers distribute links to fake websites that imitate legitimate banking or shopping services. It applies data analysis and preprocessing, performs exploratory steps, and trains predictive machine learning models using a dataset with URL and label attributes. Model quality is evaluated using confusion matrix accuracy, precision, recall, and F1 score, showing stochastic gradient descent as more effective than logistic regression.","Journal of Advanced Zoology  \nISSN: 0253-7214  \nVolume 44 IssueS-6 Year 2023 Page 930:937  \nAnalytics of Phishing Attacks Using Machine Learning  \nLingampally Shalini1*, Sunil Kumar S. Manvi2  \n1Student, Department of Computing and IT, Reva University, Bangalore-India, [1](1shaludd78@gmail.com)[shaludd78@gmail.com](1shaludd78@gmail.com), 2Director, Department of Computing and IT, Reva University, [Bangalore-India.](Bangalore-India.2ssmanvi@reva.edu.in)[2](Bangalore-India.2ssmanvi@reva.edu.in)[ssmanvi@reva.edu.in](Bangalore-India.2ssmanvi@reva.edu.in).  \n*Corresponding author’s E-mail: [shaludd78@gmail.com](shaludd78@gmail.com)  \n\n| Article History\u003Cbr>Received: 06 June 2023\u003Cbr>Revised: 05 Sept 2023\u003Cbr>Accepted: 30 Nov 2023\u003Cbr>CC License\u003Cbr>CC-BY-NC-SA 4.0 | Abstract\u003Cbr>Cyber-attacks which is known as Computer Network Attack (CAN). It is a threat created by cybercriminals by more than one computer against networks. There are various types of cyberattacks among them Phishing Attack is one of them. Phishing is a technique of gathering sensitive information of a target such as username, password, bank details etc. There are various ways to perform phishing attacks, among them URL PHISHING attack is one way to gather user’s information. Mainly hackers create a fake website regarding bank details, shopping websites, etc. using social engineering tool which looks like legitimate website. This fake URL will be sent to user via email or through some other resources. In this paper, we will be performing data analysis, data preprocessing, data exploring, training and predicting through machine learning and optimization techniques on dataset which contains two attributes (URL, Label). We will be introducing performance metrics like confusion matrix accuracy, precision, recall and F1 score to know the performance of the model. An optimization technique which is Stochastic gradient descent performed better than logistic regression.\u003Cbr>Keywords: Word Cloud, Tokenizing, Lemmatization, Logistic Regression, Stochastic Gradient Descent, etc. |\n| --- | --- |\n\n1. Introduction  \nPhishing attack is one of the cyber-attacks. There are various types of phishing attacks like email spoofing, mass phishing, URL phishing, Search engine attack, website spoofing. Phishing is one way of technique to gather the information of user like bank details, passwords, username, email ids etc. At first hacker creates a fake website which looks like a legitimate website using social engineering tools. Sending that fake website URL to the user via email or through other resources. When user clicks on that on particular fake website URL. User will be taken to the fake website and when he/she enters their personal credentials those credentials will be displayed on the terminal screen of the hacker who created fake web site. By this displayed information he/she will get access to the personal details in the absence of the user. These types of phishing attacks are the attacks which performed through URLs to gather personal credentials of the user.  \nAt First, we need to understand or get insights of URL. URL is known as Uniform Resource Locator. URL is made up of various parts like scheme, host address and file path. Here scheme determines the type of the protocol like [http](http), [https](https), ftp etc. Host address which is domain name like IP address or www. File path always starts with forward slash it may consists of directory or folder names. These are the various parts of URL. Legitimate and Phishing URL contains these parts. Legitimate URL is the trustworthy URL in which it starts with scheme like [http or](http or) [https](https) followed by colon and forward slash. Domain name like IP address or www. File path includes directory or name folders and limited number of forward slash and limited number of hyphens, limited length of URL and there are no special characters in the legitimate website. But when we talk about phishing websites URL. It mainly contains sche","cbCaipT1MJycIhWw","https://ap.wps.com/l/cbCaipT1MJycIhWw","pdf",429741,1,"English","en",105,"# Introduction\n## Overview of Phishing Attacks\n## URL Structure and Legitimate vs Phishing Characteristics\n# Materials And Methods\n## Adopted Study","[{\"question\":\"What data features does the phishing URL analytics model use?\",\"answer\":\"The dataset used contains two attributes: URL and Label, enabling supervised training for predicting whether a URL is benign or malicious.\"},{\"question\":\"How does the paper describe the difference between legitimate and phishing URLs?\",\"answer\":\"Legitimate URLs follow normal URL structure with limited slashes, limited hyphens, and fewer special characters, while phishing URLs typically show more slashes, more hyphens, and a greater number of special characters.\"},{\"question\":\"Which evaluation metrics are used to assess the machine learning model?\",\"answer\":\"Performance is measured using confusion matrix-based accuracy along with precision, recall, and the F1 score.\"}]","Analytics of Phishing Attacks Using Machine Learning | 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