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Wenqian Tian
Researcher at Beihang University
Publications - 9
Citations - 201
Wenqian Tian is an academic researcher from Beihang University. The author has contributed to research in topics: Phishing & Web page. The author has an hindex of 6, co-authored 9 publications receiving 135 citations.
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Journal ArticleDOI
Phishing-Alarm: Robust and Efficient Phishing Detection via Page Component Similarity
TL;DR: This paper presents a new solution, called Phishing-Alarm, to detect phishing attacks using features that are hard to evade by attackers, and presents an algorithm to quantify the suspiciousness ratings of Web pages based on the similarity of visual appearance between the Web pages.
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Phishing page detection via learning classifiers from page layout feature
TL;DR: A learning-based aggregation analysis mechanism to decide page layout similarity, which is used to detect phishing pages, is proposed and four popular machine learning classifiers are evaluated on their accuracy and the factors affecting their results.
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Detecting Phishing Websites via Aggregation Analysis of Page Layouts
TL;DR: This work proposes a learning-based aggregation analysis mechanism to decide page layout similarity, which is used to detect phishing pages, and shows that this approach is accurate and effective in detectingphishing pages.
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An Efficient Social Attribute Inference Scheme Based on Social Links and Attribute Relevance
TL;DR: It is found that there are relevances among social attributes, which has a great impact on inferring users’ hidden attributes, and an efficient social attribute inference scheme based on social links and attribute relevance properties is proposed.
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Understanding structure-based social network de-anonymization techniques via empirical analysis
TL;DR: A comprehensive analysis on the typical structure-based social network de-anonymization algorithms and the impacts on their application performance caused by different factors, e.g., topology properties and anonymization methods adopted to sanitize original data is conducted.