Game Theory of Data-selling Ransomware

Authors

  • Zhen Li Department of Economics and Management, Albion College, USA
  • Qi Liao Department of Computer Science, Central Michigan University, USA https://orcid.org/0000-0001-5520-157X

DOI:

https://doi.org/10.13052/jcsm2245-1439.1013

Keywords:

Cybersecurity, ransomware, ransomware 1.0, ransomware 1.5, ransomware 2.0, game theory, data selling, data threat, reputation, economics, revenue model, profit optimization

Abstract

We are experiencing the worst years of ransomware attacks with continuing news reports on high-profile ransomware attacks on organizations such as hospitals, schools, government agencies and private businesses. Recently a few ransomware attackers have gone beyond simply encrypting files and waiting for ransom. They threaten to release the data if the victims refuse their ransom request. In this paper, we propose a hypothetical new revenue model for the ransomware, i.e., selling the stolen data rather than publishing the data for free. Through a game-theoretical analysis between attackers and victims, we contribute a novel model to understand the critical decision variables for the proposed data-selling ransomware (which we refer as "ransomware 2.0") that sells data as well as demands ransom. We compare the role of reputation and the profitability of the data-selling ransomware with traditional ransomware ("ransomware 1.0") that demands ransom only and the data-threat ransomware ("ransomware 1.5") that demands ransom with the threat of releasing data for no compliance. Both theoretical modeling and simulation studies suggest that in general both ransomware 2.0 and 1.5 are more profitable than ransomware 1.0, while ransomware 2.0 is always more profitable than ransomware 1.5. Notably, common defensive measures that may work to eliminate the financial incentives of ransomware 1.0 may not work on ransomware 2.0, in particular the data backup practice and the never-pay-ransom strategy. Our findings also suggest that the uncertainties created by this new revenue model may affect attackers' reputation and users' willingness-to-pay, therefore, ransomware 2.0 may not always increase the profitability of attackers. Another finding of the study suggests that reputation maximization is critical in ransomware 1.0 and 1.5, but not in ransomware 2.0, where attackers could manipulate reputation for profit maximization.

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Author Biographies

Zhen Li, Department of Economics and Management, Albion College, USA

Zhen Li is currently an E. Maynard Aris Endowed Professor of Economics in the Department of Economics and Management at Albion College. She received her Master’s Degree and Ph.D. in Economics from Princeton University under the direction of Dr. Michael Woodford. She graduated with her Bachelor’s Degree in International Economics from Peking University. Dr. Li conducted research on applied macroeconomics and international finance, in particular on international financial integrity and related policy issues. Dr. Li’s recent research interests include inter-disciplinary research study on economics and game theory of computer networks and information security.

Qi Liao, Department of Computer Science, Central Michigan University, USA

Qi Liao is currently a Professor of Computer Science at Central Michigan University (CMU). He received his M.S. and Ph.D. in Computer Science and Engineering (CSE) from the University of Notre Dame, and a B.S. and departmental distinction in Computer Science (minor in Mathematics) from Hartwick College, New York. Dr. Liao’s research interests include computer security, machine learning, visual analytics, and economics/game theory at the intersection of network usage and cybersecurity. He received best paper awards at USENIX LISA, IEEE ICCCBDA, Emerald Literati Awards for Excellence for Information and Computer Security, IEEE VAST Challenge Award, winner of National Security Innovation Competition, Center for Research Computing Award for Computational Sciences and Visualization, and CMU College of Science & Engineering Award for Outstanding Research. Dr. Liao was a visiting research scientist at IBM Research, Argonne National Lab, and ASEE Fellow at U.S. Air Force Research Lab.

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Published

2021-03-22

How to Cite

1.
Li Z, Liao Q. Game Theory of Data-selling Ransomware. JCSANDM [Internet]. 2021 Mar. 22 [cited 2024 Apr. 20];10(1):65-96. Available from: https://journals.riverpublishers.com/index.php/JCSANDM/article/view/5933

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Section

ARES 2020 Workshops