Untagging Tor:
A Formal Treatment of Onion Encryption
Martijn Stam Jean Paul Degabriele
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Untagging Tor: A Formal Treatment of Onion Encryption Jean Paul - - PowerPoint PPT Presentation
Untagging Tor: A Formal Treatment of Onion Encryption Jean Paul Degabriele Martijn Stam 1 Outline of this talk Overview of Tor Tagging Attacks and Their Severity Modelling Onion Encryption Tor Proposal 261 and Security Analysis
Martijn Stam Jean Paul Degabriele
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Tor Network composed of Onion Routers xyz.com Onion Proxy
Four components:
K1 K1 K2 K2 K3 K3
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RELAY_EARLY (9)
(truncated SHA-1)
CMD CircID Cell Payload
4 1 509
AES-CTR (K3)
CMD CircID Encrypted Cell Payload
AES-CTR (K1)
4 1 1 2 4 2 498
CMD CircID rCMD Rec SID Digest Len Data
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xyz.com
controls some onion routers.
forwards it over.
tests if decryption succeeds.
confirmed that the two edges (CircIDs) belong to the same circuit.
OR3 OR1
effect is achieved by matching traffic patterns between input and output edges.
OR2
Onion Proxy
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against them was deemed pointless since traffic correlation attacks would be possible anyway.
the Base Rate Fallacy.
Black Hat 2009 – Tor project’s response: Nothing new here!
Attacks.
tagging attacks, eventually leading to Tor proposal 261.
2004 2008 2009 2012
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where: cells are routed individually (no circuits), onion routers are stateless, and the onion encryption is public-key.
their security definitions have a number of shortcomings.
feature – referred therein as predictable malleability.
encryption as an extension of AE, ignoring the routing aspect. 10
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n6 n4 n5 n3
! = [$6, $3, $5, $4] G(!)
. / / / / / /
OE=(G,E,D,4 D) E(. 3 , 5) (.′ 3 , $3, 7) D(/, $6, 7) 4 D(0 /[4], $6, 7) (0 /′[4], $5, 7′) 4 7 7′
against replay and reordering of cells, etc.
combination of cryptographic mechanisms and other factors such as network size and traffic load.
component contribute towards anonymity, assuming
factors to be ideal.
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An adversary should not be able to learn any new information about the circuits’ topology in the network beyond what is inevitably leaked through node corruptions. This should hold even when the adversary can choose the messages that get encrypted and is able to reorder, inject, and manipulate cells on the network. 13
Net 0 Net 1
indicates the subset that it controls.
must be the same in both networks.
adversary gets to interact with it via the corrupted nodes and tries to determine which network it is.
is significantly more complex.
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Net 0 Net 1
the following order: Orange, Black, Green, Blue.
corrupted nodes, and the order in which entries appear.
the left bottom node during decryption – can distinguish.
doesn’t leak the order in which entries are created.
15 D(!, %6, ')
' %6 ' %6
D(!, %6, ')
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tweak, updated with each cell.
(RELAY or RELAY_EARLY).
encode-then-encipher.
and Len (7 msb) – total 55 bits.
TWBC (K3)
CMD CircID Encrypted Cell Payload
TWBC (K1)
4 1 1 2 4 2 498
CMD CircID rCMD Rec SID Digest Len Data
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Tweak1 Tweak3
4 1 1 2 4 2 498
CMD CircID rCMD Rec SID Digest Len Data
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cells by switching its value from RELAY to RELAY_EARLY.
similar vulnerability was exploited in the 2014 CMU incident on Tor’s Onion Services which took down Silk Road.
but it does not prevent the attack. 18
exploitability and efficacy of this attack.
limiting the maximum circuit size.
the other mitigating factors rather than eliminate it completely.
RELAY, is circuit hiding, showing that the overall design is sound and effective against tagging attacks. 19
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reflects Tor’s use-case, identified circuit hiding as its anonymity goal, and used it to analyse Tor proposal 261.
treatment shows that the routing mechanism has significant consequences on anonymity.
different levels of abstraction, settling on distinct tradeoffs between simplicity and relevance to real world protocols (Tor). 21