Applications for Measurement: Improving Anonymity Online Rishab - - PowerPoint PPT Presentation

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Applications for Measurement: Improving Anonymity Online Rishab - - PowerPoint PPT Presentation

Oct 10, 2022 102 likes •263 views

Applications for Measurement: Improving Anonymity Online Rishab Nithyanand | Rachee Singh | Shinyoung Cho | Phillipa Gill Stony Brook University 1 Anonymity on the Internet Tor Network 2 Anonymity on the Internet Does not know the source

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SLIDE 1

Applications for Measurement: Improving Anonymity Online

Rishab Nithyanand | Rachee Singh | Shinyoung Cho | Phillipa Gill Stony Brook University

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SLIDE 2

Anonymity on the Internet

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Tor Network

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SLIDE 3

Anonymity on the Internet

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Tor Network

Does not know the destination Does not know the source

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SLIDE 4

Online Anonymity via Tor

Tor Client Server

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entry relay middle relay exit relay

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SLIDE 5

Threat Model: Network Based Attacks

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Tor Network

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SLIDE 6

Threat Model: Network Based Attacks

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Tor Network

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SLIDE 7

Threat Model: Network Based Attacks

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Tor Network

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SLIDE 8

Internet routing and timing attacks

AS1 AS4 AS3 AS5

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AS5 AS6 AS2 AS2

Tor Network

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SLIDE 9

Internet routing and timing attacks

AS1 AS4 AS3 AS5

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AS5 AS6 AS2 AS2

Tor Network

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SLIDE 10

Internet routing and timing attacks

AS1 AS4 AS3 AS5

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AS5 AS6 AS2 AS2

Path asymmetry => Increases the attack surface [RAPTOR, USENIX 2015] TCP ACK numbers leak timing and size info on reverse path!

AS5 AS5

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SLIDE 11

Astoria [NDSS2016] + Cipollino*

  • What if the Tor client could pick relays to avoid timing attacks?
  • We show that there usually is a safe option [NDSS2016]
  • Challenge:

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How can the Tor client learn network paths?

  • Astoria: Policy-based simulations on empirically derived AS graphs
  • Cipollino: Based on measured paths

* https://en.wikipedia.org/wiki/Cipollino

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Tor client measurement-plane requirements

  • Data needs to be current

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E.g., if a path changes to go through a new AS we need to know!

  • Path computations need to be local

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The client can’t ask a third party about paths to the destination!

  • Data needs to be compact + accurate
  • Trade-off between:

○ measured data as relevant as possible (near real-time). ○ Cipollino Tor client low-latency (not on-demand measurements)

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Our solution: PathCache

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  • Basic idea: Reuse measurements already being made!
  • Combine publicly accessible traceroute measurements to learn new paths

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Currently using RIPE Atlas + iPlane data

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Augmenting with control-plane data RIPE NCC, Routeviews

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Longer term: Efficient use of new measurements to increase coverage

  • http://pathcache.cs.stonybrook.edu

A B C D A D E A D E B C D

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SLIDE 14

Why is PathCache Useful?

  • Everyone needs traceroutes!
  • But why run redundant traceroutes at the expense of a constrained

measurement budget?

  • Measurement hardware can be more effectively utilised.
  • Standard and compact graphs as JSONs, easy to work with.
  • Try it out here: http://pathcache.cs.stonybrook.edu/api/v1/174 (AS174’s dest

based graph)

  • http://pathcache.cs.stonybrook.edu/api/v1/path?src=2119&dst=174

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SLIDE 15

Future Work?

  • Need more data

○ Huge benefit of periodic measurements from RIPE Atlas!

  • Path prediction as a service
  • A platform to maintain AS-level paths over time (benefit of retrospective

measurements)

  • Provide a generic interface to upload user-run measurements.
  • As a community, increase our coverage via measurement reuse

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