HinPhish: An Effective Phishing Detection Approach Based on Heterogeneous Information Networks
Autor: | Min Zhang, Yuwei Li, Chengxi Xu, Yunyi Zhang, Fan Shi, Bingyang Guo |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Technology
QH301-705.5 Computer science QC1-999 phishing Computer security computer.software_genre Resource (project management) Web page Leverage (statistics) General Materials Science malicious domain detection Side channel attack Biology (General) QD1-999 Instrumentation Fluid Flow and Transfer Processes Password Physics Process Chemistry and Technology General Engineering Construct (python library) Engineering (General). Civil engineering (General) Phishing heterogeneous information network Computer Science Applications Chemistry Information sensitivity ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS TA1-2040 computer |
Zdroj: | Applied Sciences Volume 11 Issue 20 Applied Sciences, Vol 11, Iss 9733, p 9733 (2021) |
ISSN: | 2076-3417 |
DOI: | 10.3390/app11209733 |
Popis: | Internet users have suffered from phishing attacks for a long time. Attackers deceive users through malicious constructed phishing websites to steal sensitive information, such as bank account numbers, website usernames, and passwords. In recent years, many phishing detection solutions have been proposed, which mainly leverage whitelists or blacklists, website content, or side channel-based techniques. However, with the continuous improvement of phishing technology, current methods have difficulty in achieving effective detection. Hence, in this paper, we propose an effective phishing website detection approach, which we call HinPhish. HinPhish extracts various link relationships from webpages and uses domains and resource objects to construct a heterogeneous information network. HinPhish applies a modified algorithm to leverage the characteristics of different link types in order to calculate the phish-score of the target domain on the webpage. Moreover, HinPhish not only improves the accuracy of detection, but also can increase the phishing cost for attackers. Extensive experimental results demonstrate that HinPhish can achieve an accuracy of 0.9856 and F1-score of 0.9858. |
Databáze: | OpenAIRE |
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