{"title":"电子商业环境的欺诈预防框架:自动隔离网络钓鱼企图","authors":"Nazeeh Ghatasheh","doi":"10.1109/CCC.2016.17","DOIUrl":null,"url":null,"abstract":"In the era of digital economy and high penetration rate of technology, cybercrime is taking over a great span of the cyberworld. Novice to experienced users are subject to being victims to cyber criminals. Phishing attempts lead to critical issues and risks for online users, and for companies as well. This research proposes a framework for fraud prevention by enabling the automatic detection of malicious websites. The applicability of the framework is validated by various types of experiments. The experiments tries to model phishing websites using various algorithms and approaches, including hybrid approaches. It is apparent that the performance of Random Forest Trees algorithm overperformed several other algorithms. Accordingly, the framework is proved to be useful in the segregation of malicious online content and phishing attempts. In addition the results call for more investigation and improvement in fraud prevention approaches.","PeriodicalId":120509,"journal":{"name":"2016 Cybersecurity and Cyberforensics Conference (CCC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fraud Prevention Framework for Electronic Business Environments: Automatic Segregation of Online Phishing Attempts\",\"authors\":\"Nazeeh Ghatasheh\",\"doi\":\"10.1109/CCC.2016.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the era of digital economy and high penetration rate of technology, cybercrime is taking over a great span of the cyberworld. Novice to experienced users are subject to being victims to cyber criminals. Phishing attempts lead to critical issues and risks for online users, and for companies as well. This research proposes a framework for fraud prevention by enabling the automatic detection of malicious websites. The applicability of the framework is validated by various types of experiments. The experiments tries to model phishing websites using various algorithms and approaches, including hybrid approaches. It is apparent that the performance of Random Forest Trees algorithm overperformed several other algorithms. Accordingly, the framework is proved to be useful in the segregation of malicious online content and phishing attempts. In addition the results call for more investigation and improvement in fraud prevention approaches.\",\"PeriodicalId\":120509,\"journal\":{\"name\":\"2016 Cybersecurity and Cyberforensics Conference (CCC)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Cybersecurity and Cyberforensics Conference (CCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCC.2016.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Cybersecurity and Cyberforensics Conference (CCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCC.2016.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fraud Prevention Framework for Electronic Business Environments: Automatic Segregation of Online Phishing Attempts
In the era of digital economy and high penetration rate of technology, cybercrime is taking over a great span of the cyberworld. Novice to experienced users are subject to being victims to cyber criminals. Phishing attempts lead to critical issues and risks for online users, and for companies as well. This research proposes a framework for fraud prevention by enabling the automatic detection of malicious websites. The applicability of the framework is validated by various types of experiments. The experiments tries to model phishing websites using various algorithms and approaches, including hybrid approaches. It is apparent that the performance of Random Forest Trees algorithm overperformed several other algorithms. Accordingly, the framework is proved to be useful in the segregation of malicious online content and phishing attempts. In addition the results call for more investigation and improvement in fraud prevention approaches.