# Analyzing In-browser Cryptojacking

**Authors:** Muhammad Saad, David Mohaisen  
**arXiv:** [2304.13253](https://arxiv.org/abs/2304.13253)  
**Date:** 2023-04-26  
**Summary page:** https://www.summarizepaper.com/en/paper/2304.13253v1/

## Key points

- Cryptojacking is a malicious practice where attackers exploit website visitors' processing power to mine cryptocurrencies without consent.
- The paper "Analyzing In-browser Cryptojacking" by Muhammad Saad and David Mohaisen explores this phenomenon through static, dynamic, and economic analyses.
- Static analysis techniques are used to categorize cryptojacking samples based on content, currency, and code complexity.
- Machine learning algorithms are applied to achieve 100% accuracy in distinguishing between benign, malicious, and cryptojacking JavaScript samples.

## Summary

In their paper titled "Analyzing In-browser Cryptojacking," authors Muhammad Saad and David Mohaisen delve into the intricate world of cryptojacking, a malicious practice where attackers exploit the processing power of unsuspecting website visitors to mine cryptocurrencies without their consent. The researchers conduct a comprehensive analysis of this phenomenon by examining its static, dynamic, and economic dimensions. To begin with, the authors employ static analysis techniques to categorize cryptojacking samples based on content, currency, and code complexity. This categorization allows them to assess the prevalence of these scripts across websites, identify platform preferences, and understand the intricacies of their coding structures. Through the application of machine learning algorithms, they achieve a remarkable 100% accuracy in distinguishing between benign, malicious, and cryptojacking JavaScript samples.