SoK: Cryptojacking Malware

@article{Tekiner2021SoKCM,
  title={SoK: Cryptojacking Malware},
  author={Ege Tekiner and Abbas Acar and Arif Selcuk Uluagac and Engin Kirda and Ali Aydin Selçuk},
  journal={2021 IEEE European Symposium on Security and Privacy (EuroS\&P)},
  year={2021},
  pages={120-139}
}
Emerging blockchain and cryptocurrency-based technologies are redefining the way we conduct business in cyberspace. Today, a myriad of blockchain and cryp-tocurrency systems, applications, and technologies are widely available to companies, end-users, and even malicious actors who want to exploit the computational resources of regular users through cryptojacking malware. Especially with ready-to-use mining scripts easily provided by service providers (e.g., Coinhive) and untraceable… 

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References

SHOWING 1-10 OF 178 REFERENCES

Detecting Cryptomining Using Dynamic Analysis

TLDR
The results show that browser-based cryptomining within the dataset can be detected by dynamic opcode analysis, with accuracies of up to 100%, and this is the first such work presenting op code analysis on non-executable files.

Cryptojacking injection: A paradigm shift to cryptocurrency-based web-centric internet attacks

TLDR
An attack model based on finite state machines is formulated which depicts the various breaches of confidentiality, integrity and availability in the web system as the attack progresses and shows how this new attack vector attacks some of the core components of e-commerce to generate Monero crypto currency from benign web users.

Dine and Dash: Static, Dynamic, and Economic Analysis of In-Browser Cryptojacking

TLDR
An analytical model is built to empirically evaluate the feasibility of cryptojacking as an alternative to online advertisement and shows a large negative profit and loss gap, indicating that the model is economically impractical.

Crypto Mining Makes Noise

TLDR
This work identifies and model a new type of attack, i.e., the sponge-attack, being a generalization of cryptojacking, and proposes Crypto-Aegis, a Machine Learning (ML) based framework that builds over the previous steps to detect crypto-mining activities.

CoinPolice: Detecting Hidden Cryptojacking Attacks with Neural Networks

TLDR
A novel detection method, CoinPolice, that is robust against all of the aforementioned evasion techniques, and deployed to perform the largest-scale cryptoming investigation to date, identifying 6700 sites that monetize traffic in this fashion.

MineSweeper: An In-depth Look into Drive-by Cryptocurrency Mining and Its Defense

TLDR
A comprehensive analysis on Alexa's Top 1 Million websites to shed light on the prevalence and profitability of drive-by mining, and presents MineSweeper, a novel detection technique that is based on the intrinsic characteristics of cryptomining code, and, thus, is resilient to obfuscation.

Ransomware Payments in the Bitcoin Ecosystem

TLDR
A data-driven method for identifying and gathering information on Bitcoin transactions related to illicit activity based on footprints left on the public Bitcoin blockchain is presented and found that the market is highly skewed with only a few number of players responsible for the majority of the payments.

A First Look at the Crypto-Mining Malware Ecosystem: A Decade of Unrestricted Wealth

TLDR
The largest measurement of crypto-mining malware to date is conducted, analyzing approximately 4.5 million malware samples over a period of twelve years from 2007 to 2019, showing that a high proportion of this ecosystem is supported by underground economies such as Pay-Per-Install services.

An Experimental Analysis of Cryptojacking Attacks

TLDR
The results show that a well-configured cryptojacking attack does not significantly harm its victims, hence can be very difficult to detect, and even aware users might not bother getting rid of the infection.
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