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Collusion Attack from Hubs in the Blockchain Offline Channel Network

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The 1st International Conference on
Mathematical Research for Blockchain Economy / Fira, Santorini / 9th May 2019

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Collusion Attack from Hubs in the Blockchain Offline Channel Network

  1. 1. Subhasis Thakur and John Breslin Data Science Institute National University of Ireland Galway Collusion attack from hubs in the blockchain offline channel network
  2. 2. “Collusion practices in a West of Ireland livestock mart” - Curtin & Varley, 1982 2
  3. 3. Scalability problem 3
  4. 4. Offline channels 4
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  19. 19. 19 Bitcoin Lightning Network
  20. 20. 20 Hubs in Lightning Network
  21. 21. 21 Research problem: collusion (eclipse) attack ● Can a collusion of hubs execute a collusion attack against another set of hubs?
  22. 22. Results ● Mathematical model of collusion attack on the channel network ● Likelihood of collusion attack using Banzhaf indices ● We found that there are 62 nodes who can execute collusion attacks against 90% of their neighbours in the Lightning Network 22
  23. 23. 23 Model of collusion attack Neighborhood of Vi with distance d
  24. 24. 24 Model of collusion attack Targets of a collusion attack is a pair of hubs in its neighborhood
  25. 25. 25 Model of collusion attack Vi forms a collusion to produce a cut between hubs V1 and V2 in its neighborhood
  26. 26. 26 Model of collusion attack: how likely that a hub can orch- estrate an attack? Collusion formation as a cooperative game
  27. 27. 27 Ability to orchestrate collusion = Banzhaf index
  28. 28. 28 Banzhaf index Banzhaf index = (Number of coalitions where Vi is a critical player) / (Number of coalitions where Vi is a member)
  29. 29. 29 Banzhaf index (in terms of the ability to orchestrate collusion) Banzhaf index = (Number of collusions where Vi is a critical player) / (Number of collusions where Vi is a member)
  30. 30. 30 Potential of collusion attacks A high standard deviation would indicate that there are few hubs who can easily execute a collusion attack while the remaining hubs are unlikely to execute collusion attack
  31. 31. 31 ● The probability that a hub can successfully execute a collusion attack increases as its degree increases ● If hubs of the hub network have a uniform degree then, Banzhaf indices are approximately equal ● Uniform Banzhaf indices may prevent collusion attacks in the hub network Method to reduce possibility of collusion attacks
  32. 32. 32 Evaluation: data Bitcoin Lightning Network (1st March 2019) ● # nodes = 2810 ● # edges = 22596 ● Average degree = 16 ● Minimum degree = 1 ● Maximum degree = 961
  33. 33. 33 Evaluation: algorithm to compute the Banzhaf index
  34. 34. ● Relation between the Banzhaf index and the diameter of the network ● The uniformity of Banzhaf increases as the diameter of the network decreases 34
  35. 35. 35 Vulnerability due to collusion attack Vulnerability w.r.t. node Vi = (# of neighbours with a Banzhaf index less than Vi ) / (Size of neighbourhood of Vi )
  36. 36. 36 ● There are 62 nodes who can execute collusion attacks against 90% of their neighbors in the Lightning Network
  37. 37. 37 Thank you: any questions? subhasis.thakur@nuigalway.ie john.breslin@nuigalway.ie

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