CRIRSINov 13, 2021

Evaluating the effectiveness of Phishing Reports on Twitter

arXiv:2111.07201v212 citationsHas Code
AI Analysis

This work addresses phishing detection for cybersecurity by analyzing social media data, but it is incremental as it builds on existing feeds.

The study evaluated phishing reports on Twitter, finding they contain more information and unique URLs compared to existing feeds, but have low user interaction and many URLs remain active for over a week.

Phishing attacks are an increasingly potent web-based threat, with nearly 1.5 million websites created on a monthly basis. In this work, we present the first study towards identifying such attacks through phishing reports shared by users on Twitter. We evaluated over 16.4k such reports posted by 701 Twitter accounts between June to August 2021, which contained 11.1k unique URLs, and analyzed their effectiveness using various quantitative and qualitative measures. Our findings indicate that not only do these users share a high volume of legitimate phishing URLs, but these reports contain more information regarding the phishing websites (which can expedite the process of identifying and removing these threats), when compared to two popular open-source phishing feeds: PhishTank and OpenPhish. We also notice that the reported websites had very little overlap with the URLs existing in the other feeds, and also remained active for longer periods of time. But despite having these attributes, we found that these reports have very low interaction from other Twitter users, especially from the domains and organizations targeted by the reported URLs. Moreover, nearly 31% of these URLs were still active even after a week of them being reported, with 27% of them being detected by very few anti-phishing tools, suggesting that a large majority of these reports remain undiscovered, despite the majority of the follower base of these accounts being security focused users. Thus, this work highlights the effectiveness of the reports, and the benefits of using them as an open source knowledge base for identifying new phishing websites.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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