Network Partitioning E ff ects on Ripple Transactions Yoan Martin - - PowerPoint PPT Presentation

network partitioning e ff ects on ripple transactions
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Network Partitioning E ff ects on Ripple Transactions Yoan Martin - - PowerPoint PPT Presentation

Network Partitioning E ff ects on Ripple Transactions Yoan Martin 1 Todays menu What is Ripple? Why is it interesting? Attacks Analysis 2 What is Ripple? Global Payments Network RippleNet vs XRP Gateway


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Network Partitioning Effects

  • n Ripple Transactions

Yoan Martin

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Today’s menu

  • What is Ripple?
  • Why is it interesting?
  • Attacks
  • Analysis

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What is Ripple?

  • Global Payments Network
  • RippleNet vs XRP
  • Gateway
  • Entry Point
  • Ripple Bank

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Why is it interesting?

  • More than 200 financial institutions
  • ~20’000’000 USD sent by hour
  • Take place on internet

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What is the network?

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Network

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What is the network?

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Attacks

  • What if an AS is malicious?
  • What can it do?
  • Dropping the traffic
  • BGP Hijacking

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Traffic dropped

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Traffic dropped

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BGP Hijacking

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A B

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BGP Hijacking

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A B

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BGP Hijacking

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A B

I know B!

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BGP Hijacking

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A B

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How to measure the effect?

  • Build the Ripple Network
  • Ripple API
  • Caida
  • Use previous transactions
  • Replay transactions when an attack occurs

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Build RippleNet

Ripple API, Gateways data AS relationships AS AS with a Gateway

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Map Result

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Transactions

  • Account A sends 100 XRP to account B
  • Some transactions have gateways data
  • Account A sends 100 XRP using Gateway G to B
  • Account B receives 100 XRP using Gateway H from A
  • Keep only transactions with matching Gateways

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Simulation : traffic dropped

A sends 100 XRP to B D sends 10 USD to A C sends 4 EUR to B … A sends 100 XRP to B D sends 10 USD to A C sends 4 EUR to B …

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Simulation : traffic dropped

  • If == , transaction is complete
  • If != , transaction is rerouted
  • If no , transaction is lost

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Example of results

Completed Rerouted Lost Amazon 10% 10% 80% AT&T 30% 20% 50% China Telecom 60% 30% 10% Swisscom 30% 30% 40%

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Simulation: BGP Hijacking

A sends 100 XRP to B D sends 10 USD to A C sends 4 EUR to B …

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Simulation: BGP Hijacking

  • If == , transaction is complete
  • If != , transaction is rerouted

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Example of results

Completed Rerouted Amazon 90% 10% AT&T 60% 40% China Telecom 20% 80% Swisscom 30% 70%

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Real Results

  • Transactions analysis
  • Which ASes are the most dangerous?
  • What is the effect on the Ripple network?

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Transactions analysis

  • % of transactions with AS as

sender or receiver

  • 13335 is Cloudflare (US)
  • 19551 is Incapsula (US)

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Which ASes are dangerous? Traffic dropped

  • % transactions lost

corresponds to transactions distribution

  • Lost if gateways in

corrupted node

  • Never lost if intermediaries
  • Always possible to find

a path

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Which ASes are dangerous? Traffic dropped

  • Little % of rerouted

transactions

  • Certainly due to transactions

distribution

  • 553 is Belwue (DE)
  • Connections with 680 ISP
  • Switch, Swisscom

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Which ASes are dangerous? BGP Hijacking

  • Many ASes can corrupt the network
  • Long list of ASes reach almost 40% of rerouted transactions

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What is the effect on Ripple?

  • Time analysis
  • On average low effect

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Conclusion

  • Most of the transactions go through 2 ASes
  • Big impact if one of them is corrupted
  • BGP Hijacking has more effect than traffic dropped
  • Limitations of this analysis
  • Network only considers Gateways
  • Hence, only a few transactions are considered

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Thank you for your attention

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White gap?

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BGP Hijacking : August ?

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