I'm SPARTACUS, No, I'm SPARTACUS: Proactively Protecting Users from Phishing by Intentionally Triggering Cloaking Behavior
I'm SPARTACUS, No, I'm SPARTACUS: Proactively Protecting Users from Phishing by Intentionally Triggering Cloaking Behavior
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我是斯巴达克斯,不,我是斯巴达克斯:通过故意触发伪装行为主动保护用户免受网络钓鱼
DOI:
10.1145/3548606.3559334
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发表时间:
2022
期刊:
影响因子:
--
通讯作者:
Shoshitaishvili, Yan
中科院分区:
文献类型:
--
作者:
Zhang, Penghui;Sun, Zhibo;Kyung, Sukwha;Behrens, Hans Walter;Basque, Zion Leonahenahe;Cho, Haehyun;Oest, Adam;Wang, Ruoyu;Bao, Tiffany;Shoshitaishvili, Yan
Phishing is a ubiquitous and increasingly sophisticated online threat. To evade mitigations, phishers try to "cloak" malicious content from defenders to delay their appearance on blacklists, while still presenting the phishing payload to victims. This cat-and-mouse game is variable and fast-moving, with many distinct cloaking methods---we construct a dataset identifying 2,933 real-world phishing kits that implement cloaking mechanisms. These kits use information from the host, browser, and HTTP request to classify traffic as either anti-phishing entity or potential victim and change their behavior accordingly.In this work we present SPARTACUS, a technique that subverts the phishing status quo by disguising user traffic as anti-phishing entities. These intentional false positives trigger cloaking behavior in phishing kits, thus hiding the malicious payload and protecting the user without disrupting benign sites.To evaluate the effectiveness of this approach, we deployed SPARTACUS as a browser extension from November 2020 to July 2021. During that time, SPARTACUS browsers visited 160,728 reported phishing URLs in the wild. Of these, SPARTACUS protected against 132,274 sites (82.3%). The phishing kits which showed malicious content to SPARTACUS typically did so due to ineffective cloaking---the majority (98.4%) of the remainder were detected by conventional anti-phishing systems such as Google Safe Browsing or VirusTotal, and would be blacklisted regardless. We further evaluate SPARTACUS against benign websites sampled from the Alexa Top One Million List for impacts on latency, accessibility, layout, and CPU overhead, finding minimal performance penalties and no loss in functionality.
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DOI:
--
发表时间:
2007
期刊:
Security, Privacy, and Trust in Modern Data Management
影响因子:
--
作者:
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通讯作者:
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DOI:
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发表时间:
2015
期刊:
2015 IEEE International Congress on Big Data
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2011
期刊:
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DOI:
10.1109/eurosp.2017.26
发表时间:
2017-04
期刊:
2017 IEEE European Symposium on Security and Privacy (EuroS&P)
影响因子:
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通讯作者:
Georg Merzdovnik;Markus Huber;D. Buhov;Nick Nikiforakis;S. Neuner;Martin Schmiedecker;E. Weippl
DOI:
10.1145/1242572.1242659
发表时间:
2007-05
期刊:
--
影响因子:
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作者:
Yue Zhang;Jason I. Hong;L. Cranor
通讯作者:
Yue Zhang;Jason I. Hong;L. Cranor