Circuit: A JavaScript Memory Heap-Based Approach for Precisely Detecting Cryptojacking Websites

Hyunji Hong, Seunghoon Woo, Sunghan Park, Jeongwook Lee, Heejo Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Cryptojacking is often used by attackers as a means of gaining profits by exploiting users' resources without their consent, despite the anticipated positive effect of browser-based cryptomining. Previous approaches have attempted to detect cryptojacking websites, but they have the following limitations: (1) they failed to detect several cryptojacking websites either because of their evasion techniques or because they cannot detect JavaScript-based cryptojacking and (2) they yielded several false alarms by focusing only on limited characteristics of cryptojacking, such as counting computer resources. In this paper, we propose CIRCUIT, a precise approach for detecting cryptojacking websites. We primarily focuse on the JavaScript memory heap, which is resilient to script code obfuscation and provides information about the objects declared in the script code and their reference relations. We then extract a reference flow that can represent the script code behavior of the website from the JavaScript memory heap. Hence, CIRCUIT determines that a website is running cryptojacking if it contains a reference flow for cryptojacking. In our experiments, we found 1,813 real-world cryptojacking websites among 300K popular websites. Moreover, we provided new insights into cryptojacking by modeling the identified evasion techniques and considering the fact that characteristics of cryptojacking websites now appear on normal websites as well.

Original languageEnglish
Pages (from-to)95356-95368
Number of pages13
JournalIEEE Access
Volume10
DOIs
Publication statusPublished - 2022

Bibliographical note

Funding Information:
This work was supported in part by the Institute of Information and Communications Technology Planning and Evaluation (IITP) by the Korean Government through the Development of Automated Vulnerability Discovery Technologies for Blockchain Platform Security under Grant 2019-0-01697, in part by the Development of Software Bill of Materials (SBOM) Technologies for Securing Software Supply Chains under Grant 2022-0-00277, in part by the Convergence Security Core Talent Training Business under Grant 2022-0-01198, and in part by the ICT Creative Consilience Program under Grant IITP-2022-2020-0-01819.

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Browser security
  • cryptojacking
  • web security

ASJC Scopus subject areas

  • General Engineering
  • General Materials Science
  • General Computer Science

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