Paper Info
Title
MineSweeper: An In-depth Look into Drive-by Cryptocurrency Mining and Its Defense.
Abstract
A wave of alternative coins that can be effectively mined without specialized hardware, and a surge in cryptocurrencies' market value has led to the development of cryptocurrency mining ( cryptomining ) services, such as Coinhive, which can be easily integrated into websites to monetize the computational power of their visitors. While legitimate website operators are exploring these services as an alternative to advertisements, they have also drawn the attention of cybercriminals: drive-by mining (also known as cryptojacking ) is a new web-based attack, in which an infected website secretly executes JavaScript code and/or a WebAssembly module in the user's browser to mine cryptocurrencies without her consent. In this paper, we perform a comprehensive analysis on Alexa's Top 1 Million websites to shed light on the prevalence and profitability of this attack. We study the websites affected by drive-by mining to understand the techniques being used to evade detection, and the latest web technologies being exploited to efficiently mine cryptocurrency. As a result of our study, which covers 28 Coinhive-like services that are widely being used by drive-by mining websites, we identified 20 active cryptomining campaigns. Motivated by our findings, we investigate possible countermeasures against this type of attack. We discuss how current blacklisting approaches and heuristics based on CPU usage are insufficient, and present MineSweeper, a novel detection technique that is based on the intrinsic characteristics of cryptomining code, and, thus, is resilient to obfuscation. Our approach could be integrated into browsers to warn users about silent cryptomining when visiting websites that do not ask for their consent.
Year
DOI
Venue
2018
10.1145/3243734.3243858
ACM Conference on Computer and Communications Security
Keywords
Field
DocType
cryptocurrency, mining, cryptojacking, drive-by attacks, malware
Countermeasure,Computer security,Computer science,Profitability index,Heuristics,Blacklisting,Malware,Cryptocurrency,Obfuscation,JavaScript
Conference
ISBN
Citations 
PageRank 
978-1-4503-5693-0
14
0.91
References 
Authors
15
7
Name
Order
Citations
PageRank
Radhesh Krishnan Konoth1172.29
Emanuele Vineti2140.91
Veelasha Moonsamy31077.75
Martina Lindorfer4834.62
Christopher Kruegel58799516.05
Herbert Bos62127122.81
Giovanni Vigna77121507.72