{"title":"网络钓鱼检测及特征选择在数据挖掘分类算法中的重要性综述","authors":"","doi":"10.46243/jst.2020.v5.i6.pp11-18","DOIUrl":null,"url":null,"abstract":": In this era of Internet, the issue of security of information is at its peak. One of the main threats in this\ncyber world is phishing attacks which is an email or website fraud method that targets the genuine webpage or an\nemail and hacks it without the consent of the end user. There are various techniques which help to classify whether\nthe website or an email is legitimate or fake. The major contributors in the process of detection of these phishing\nfrauds include the classification algorithms, feature selection techniques or dataset preparation methods and the\nfeature extraction that plays an important role in detection as well as in prevention of these attacks. This Survey\nPaper studies the effect of all these contributors and the approaches that are applied in the study conducted on the\nrecent papers. Some of the classification algorithms that are implemented includes Decision tree, Random Forest ,\nSupport Vector Machines, Logistic Regression , Lazy K Star, Naive Bayes and J48 etc.","PeriodicalId":23534,"journal":{"name":"Volume 5, Issue 4","volume":"97 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Survey on Phishing Detection and The Importance of Feature\\nSelection In Data Mining Classification Algorithms\",\"authors\":\"\",\"doi\":\"10.46243/jst.2020.v5.i6.pp11-18\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": In this era of Internet, the issue of security of information is at its peak. One of the main threats in this\\ncyber world is phishing attacks which is an email or website fraud method that targets the genuine webpage or an\\nemail and hacks it without the consent of the end user. There are various techniques which help to classify whether\\nthe website or an email is legitimate or fake. The major contributors in the process of detection of these phishing\\nfrauds include the classification algorithms, feature selection techniques or dataset preparation methods and the\\nfeature extraction that plays an important role in detection as well as in prevention of these attacks. This Survey\\nPaper studies the effect of all these contributors and the approaches that are applied in the study conducted on the\\nrecent papers. Some of the classification algorithms that are implemented includes Decision tree, Random Forest ,\\nSupport Vector Machines, Logistic Regression , Lazy K Star, Naive Bayes and J48 etc.\",\"PeriodicalId\":23534,\"journal\":{\"name\":\"Volume 5, Issue 4\",\"volume\":\"97 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 5, Issue 4\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46243/jst.2020.v5.i6.pp11-18\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 5, Issue 4","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46243/jst.2020.v5.i6.pp11-18","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Survey on Phishing Detection and The Importance of Feature
Selection In Data Mining Classification Algorithms
: In this era of Internet, the issue of security of information is at its peak. One of the main threats in this
cyber world is phishing attacks which is an email or website fraud method that targets the genuine webpage or an
email and hacks it without the consent of the end user. There are various techniques which help to classify whether
the website or an email is legitimate or fake. The major contributors in the process of detection of these phishing
frauds include the classification algorithms, feature selection techniques or dataset preparation methods and the
feature extraction that plays an important role in detection as well as in prevention of these attacks. This Survey
Paper studies the effect of all these contributors and the approaches that are applied in the study conducted on the
recent papers. Some of the classification algorithms that are implemented includes Decision tree, Random Forest ,
Support Vector Machines, Logistic Regression , Lazy K Star, Naive Bayes and J48 etc.