Cryptology ePrint Archive: Report 2020/1614

SoK: Algorithmic Incentive Manipulation Attacks on Permissionless PoW Cryptocurrencies

Aljosha Judmayer and Nicholas Stifter and Alexei Zamyatin and Itay Tsabary and Ittay Eyal and Peter Gaži and Sarah Meiklejohn and Edgar Weippl

Abstract: A long standing question in the context of cryptocurrencies based on Nakamoto consensus is whether such constructions are incentive compatible, i.e., the intended properties of the system emerge from the appropriate utility model for participants. Bribing and other related attacks, such as front-running or Goldfinger attacks, aim to directly influence the incentives of actors within (or outside) of the targeted cryptocurrency system. The theoretical feasibility of bribing attacks on cryptocurrencies was first highlighted in 2016 by Bonneau, with various different techniques and approaches having since been proposed. Some of these attacks are designed to gain in-band profits, while others intend to break the mechanism design and render the cryptocurrency worthless. In this paper, we systematically expose the large but scattered body of research in this area which has accumulated over the years. We summarize these bribing attacks and similar techniques that leverage on programmatic execution and verification under the term algorithmic incentive manipulation (AIM) attacks, and show that the problem space is not yet fully explored. Based on our analysis we present several research gaps and opportunities that warrant further investigation. In particular, we highlight no- and near-fork attacks as a powerful, yet largely underestimated, AIM category that raises serious security concerns not only for smart contract platforms.

Category / Keywords: applications / Cryptocurrencies, algorithmic incentive manipulation, bribing, bribing, game theory, mechanism design

Date: received 29 Dec 2020, last revised 31 Dec 2020

Contact author: ajudmayer at sba-research org

Available format(s): PDF | BibTeX Citation

Note: This systematization is an updated and extended version of the extensive related work which was previously part of this paper:

Version: 20201231:090925 (All versions of this report)

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