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Title:
an intelligent anti-phishing strategy model for phishing website detection
Author: Zhuang Weiwei ; Jiang Qingshan ; Xiong Tengke
Source: Proceedings - 32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012
Conference Name: 32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012
Conference Date: June 18, 2012 - June 21, 2012
Issued Date: 2012
Conference Place: Macau, China
Keyword: Security of data ; Websites
Indexed Type: EI
Department: (1) Department of Cognitive Science Xiamen University Xiamen 361005 China; (2) Shenzhen Institutes of Advanced Technology (SIAT) Chinese Academy of Sciences Shenzhen 518055 China; (3) Software School of Xiamen University Xiamen University Xiamen 361005 China
Sponsorship: IEEE Comput. Soc. Tech. Comm. Distrib. Process.
Abstract: As a new form of malicious software, phishing websites appear frequently in recent years, which cause great harm to online financial services and data security. In this paper, we design and implement an intelligent model for detecting phishing websites. In this model, we extract 10 different types of features such as title, keyword and link text information to represent the website. Heterogeneous classifiers are then built based on these different features. We propose a principled ensemble classification algorithm to combine the predicted results from different phishing detection classifiers. Hierarchical clustering technique has been employed for automatic phishing categorization. Case studies on large and real daily phishing websites collected from King soft Internet Security Lab demonstrate that our proposed model outperforms other commonly used anti-phishing methods and tools in phishing website detection. © 2012 IEEE.
English Abstract: As a new form of malicious software, phishing websites appear frequently in recent years, which cause great harm to online financial services and data security. In this paper, we design and implement an intelligent model for detecting phishing websites. In this model, we extract 10 different types of features such as title, keyword and link text information to represent the website. Heterogeneous classifiers are then built based on these different features. We propose a principled ensemble classification algorithm to combine the predicted results from different phishing detection classifiers. Hierarchical clustering technique has been employed for automatic phishing categorization. Case studies on large and real daily phishing websites collected from King soft Internet Security Lab demonstrate that our proposed model outperforms other commonly used anti-phishing methods and tools in phishing website detection. © 2012 IEEE.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15964
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Zhuang Weiwei,Jiang Qingshan,Xiong Tengke. an intelligent anti-phishing strategy model for phishing website detection[C]. 见:32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012. Macau, China. June 18, 2012 - June 21, 2012.
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