End-to-End Analysis of In-Browser Cryptojacking
Muhammad Saad, Aminollah Khormali, Aziz Mohaisen

TL;DR
This paper provides a comprehensive analysis of in-browser cryptojacking, revealing its widespread nature, technical features, economic implications, and evaluating countermeasures to combat this growing threat.
Contribution
It offers the first systematic static and dynamic analysis of cryptojacking, including detection techniques and economic feasibility assessment, filling a significant research gap.
Findings
Cryptojacking is widespread across various website types.
Most cryptojacking sites use Coinhive to mine Monero.
Cryptojacking scripts have unique code complexity features with 96.4% detection accuracy.
Abstract
In-browser cryptojacking involves hijacking the CPU power of a website's visitor to perform CPU-intensive cryptocurrency mining, and has been on the rise, with 8500% growth during 2017. While some websites advocate cryptojacking as a replacement for online advertisement, web attackers exploit it to generate revenue by embedding malicious cryptojacking code in highly ranked websites. Motivated by the rise of cryptojacking and the lack of any prior systematic work, we set out to analyze malicious cryptojacking statically and dynamically, and examine the economical basis of cryptojacking as an alternative to advertisement. For our static analysis, we perform content-, currency-, and code-based analyses. Through the content-based analysis, we unveil that cryptojacking is a wide-spread threat targeting a variety of website types. Through a currency-based analysis we highlight affinities…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Web Application Security Vulnerabilities · Security and Verification in Computing
