Parasite Chain Detection in the IOTA Protocol

Authors Andreas Penzkofer, Bartosz Kusmierz, Angelo Capossele, William Sanders, Olivia Saa

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Author Details

Andreas Penzkofer
  • IOTA Foundation, Berlin, Germany
Bartosz Kusmierz
  • Department of Theoretical Physics, Wroclaw University of Science and Technology, Poland
Angelo Capossele
  • IOTA Foundation, Berlin, Germany
William Sanders
  • IOTA Foundation, Berlin, Germany
Olivia Saa
  • Department of Applied Mathematics, Institute of Mathematics and Statistics, University of São Paulo, Brazil

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Andreas Penzkofer, Bartosz Kusmierz, Angelo Capossele, William Sanders, and Olivia Saa. Parasite Chain Detection in the IOTA Protocol. In 2nd International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2020). Open Access Series in Informatics (OASIcs), Volume 82, pp. 8:1-8:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


In recent years several distributed ledger technologies based on directed acyclic graphs (DAGs) have appeared on the market. Similar to blockchain technologies, DAG-based systems aim to build an immutable ledger and are faced with security concerns regarding the irreversibility of the ledger state. However, due to their more complex nature and recent popularity, the study of adversarial actions has received little attention so far. In this paper we are concerned with a particular type of attack on the IOTA cryptocurrency, more specifically a Parasite Chain attack that attempts to revert the history stored in the DAG structure, also called the Tangle. In order to improve the security of the Tangle, we present a detection mechanism for this type of attack. In this mechanism, we embrace the complexity of the DAG structure by sampling certain aspects of it, more particularly the distribution of the number of approvers. We initially describe models that predict the distribution that should be expected for a Tangle without any malicious actors. We then introduce metrics that compare this reference distribution with the measured distribution. Upon detection, measures can then be taken to render the attack unsuccessful. We show that due to a form of the Parasite Chain that is different from the main Tangle it is possible to detect certain types of malicious chains. We also show that although the attacker may change the structure of the Parasite Chain to avoid detection, this is done so at a significant cost since the attack is rendered less efficient.

Subject Classification

ACM Subject Classification
  • Networks → Security protocols
  • Distributed ledger technology
  • cryptocurrency
  • directed acyclic graph
  • security
  • attack detection algorithm


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