{"title":"多阶段网络钓鱼URL预测的机器学习","authors":"Khalid Amen, Mohamad Zohdy, M. Mahmoud","doi":"10.1109/CSCI54926.2021.00049","DOIUrl":null,"url":null,"abstract":"Phishing is a fraudulent process and a form of cybercrime where an attacker tries to obtain sensitive information for malicious use. A phisher uses social engineering and technical deception to fetch private information from the web user. Previous Machine Learning (ML) approaches have been used to detect whether URLs are valid, or invalid. The purpose of this work is to detect, or predict, the three stages of Phishing URLs starting with valid, not enough info and invalid URLs. We will investigate different potential models that are trained by Machine Learning algorithms and find out which of these models has better accuracy.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine Learning for Multiple Stage Phishing URL Prediction\",\"authors\":\"Khalid Amen, Mohamad Zohdy, M. Mahmoud\",\"doi\":\"10.1109/CSCI54926.2021.00049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Phishing is a fraudulent process and a form of cybercrime where an attacker tries to obtain sensitive information for malicious use. A phisher uses social engineering and technical deception to fetch private information from the web user. Previous Machine Learning (ML) approaches have been used to detect whether URLs are valid, or invalid. The purpose of this work is to detect, or predict, the three stages of Phishing URLs starting with valid, not enough info and invalid URLs. We will investigate different potential models that are trained by Machine Learning algorithms and find out which of these models has better accuracy.\",\"PeriodicalId\":206881,\"journal\":{\"name\":\"2021 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSCI54926.2021.00049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI54926.2021.00049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine Learning for Multiple Stage Phishing URL Prediction
Phishing is a fraudulent process and a form of cybercrime where an attacker tries to obtain sensitive information for malicious use. A phisher uses social engineering and technical deception to fetch private information from the web user. Previous Machine Learning (ML) approaches have been used to detect whether URLs are valid, or invalid. The purpose of this work is to detect, or predict, the three stages of Phishing URLs starting with valid, not enough info and invalid URLs. We will investigate different potential models that are trained by Machine Learning algorithms and find out which of these models has better accuracy.