Research on Phishing Websitedetection Based on R-SVM algorithm. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Hu, Shuting; Li, Jiawei; Liu, Mingmeng; Pan, Bin
• Is Part Of: Journal of physics. Volume 1757:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Phishing websitesdetection -- SVM -- R-SVM Algorithm -- Network Security; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1757/1/012058
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The Internet has brought us convenience, at the same timeimportant personal information has been exposed. Once the information is leaked, it may cause huge economic losses to individuals. Therefore, it is urgent to realize network security. The traditional method of detecting phishing websites is aimed at big data. Due to the relatively large amount of data, it indirectly causes low efficiency and often fails to solve user needs in a short time. In the detection, the operation is actually performed on the small data stream. If the small data is fundamentally classified, the efficiency will be greatly improved. In summary, based on the realization that we can identify phishing websites, we mainly solve the problems of speed and accuracy. Therefore, this paper uses the R-SVM algorithm to study the data to reduce the time spent on detecting samples and improve efficiency.