a potential technique to deanonymise users of the tor network · hop in the tor network • we...

UK TOP SECRET STRAPl COMINT

A potential technique to deanonymise users of the TOR network

OPC-MCR, GCHQ

This information is exempt from disclosure under the Freedom of Information Act 2000 and other UK information legislation. Refer disclosure requests to GCHQ on

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Outline

• TOR and the need for deanonymisation • Data transformation • Scoring

• Results

• Current status • Software

This information is exempt from disclosure under the Freedom of Information Act 2000 and other UK information legislation. Refer disclosure requests to GCHQ



What is TOR?

• "The Onion Router" • Hides source of traffic by passing encrypted

versions of your internet traffic between multiple TOR routers

• Notation: - "Client" -the initiator of communication - "Guard node" -the TOR router the client contacts - "Exit node" - the TOR router that relays your traffic to

the final destination (with no extra encryption so this link can be exploited by SIGINT system)

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G ( H Q © Crown Copyright. All rights reserved.

Client

UK SECRET STRAPl COMINT

What is TOR? Guard Node~

-

Onion Router · """"""'"

A

Onion Router

B

•. H .. .. .. .. · .... .. ..... •i!•

Onion Router



Exit Node

Server


Who uses TOR?

• TOR was created by the US government and is now maintained by the Electronic Frontier Foundation (EFF)

• EFF will tell you there are many pseudo-legitimate uses for TOR

• We're interested as bad people use TOR, in particular: - Terrorists - Paedophiles




Aim

• Find client IP address associated with TOR exit node traffic

• Attack based on externals - specifically packet timings - Strong crypt is being used

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Aim

• We'll make our task easier by assuming we own the exit node being used - Allows us to see all the traffic associated with a TOR

circuit - Demultiplex traffic by (unknown) user

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Side note: Circuit tracing

• One suggestion was to track packets through each hop in the TOR network

• We experimented with spotting all links in circuits created by GCHQ

• Visibility was too low to be a sensible approach - 13 out of 8294 potential inter-TOR-router links were seen

• We will directly correlate: - exit node traffic, and

- traffic between client and guard node



UK SECRET STRAPl COMINT

Guard Node Client Onion

Router A

Collect through SIGINT

Onion Router

B



Own this node

xit Node

Server


Test data collection

• Used the standard "TOR button" web-browser package to access TOR

• Made minor changes to ensure we could collect exit node traffic 1. "News": Search for news, visit news websites 2. "TOR": Browse the TOR website and then use a privacy

checking website • Split into 2a and 2b as TOR changed circuit mid-way through

1. "Download": visit to Slash Dot followed by downloading a large PDF file.

2. "Forum": Search on Google followed by browsing a PC technical help forum.

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Flattening of timing patterns

• (ICTR-NE) observed that TOR can flatten out timing patterns

• TOR uses a rate-limiting store-and-forward procedure at each TOR router

• Graph shows bytes of exit node traffic in green and client traffic in red whilst downloading a 1MB file (fiqure from

r

1-

,, ld1i l IIIII IIIIIL IIIidl l r1ll,,l1 il Lilli lr lrll llrl,flrlrrdlllll lliilfl,lll l I Ill,,, IIIII IIIII .. 1111111 IIIII IIIII I IIIII I IIIII IIII I IIIII I llllllllllllllllillllilllilll, I I I I

Os 5 0 ; 1005 150s 200s



50000

25000

0


Cumulative packet cou n~s

• Our new insight is to use cumulative packet counts

• Hope packets are approximately preserved - Approximate as TOR

repacketises data

• See strong correlation

Ex it -Guard -

~j~Ct~os--------~,~ ~j~St~oc--------~1

I I I I I I I I I

15:46 15:48 15 :50 15:52 15:54 15 :56 15:46 15:48 15:50 15:52 15 :54 15:56

-~i7--lal~r~ la

C: I I I L....:.......,-1 -----,1-------,--1 __ ___J

g 16:02 16:04 16:06 16:02 16:04 16:06

f ;Cos , ~bl ~foc , ~b l E 16:02 16:04 16:06 16:08 16:02 16:04 16:06 16:08

a;ros ' ;~:/l!roc' ~3 16:12 16:14 16:16 16:18 16:12 16:14 16:16 16:18

~fos 4J~f'oc ~4 I I I~ I I I I

16:22 16:24 16:26 16 28 16:22 16:24 16:26 16:28

T ime (hh :mm)




Scoring: basic idea

• An idea of - Bin time into intervals - For each interval get a pair (Ei, Gi)

• Cumulative exit node packets upto time i • Cumulative guard node packets upto time i

- Measure the correlation between these pairs

• We use ls time-windows - Easy for the SIGINT system -Seems to work




Scoring: refinements

• We also expect counts to be similar Fit a linear model

• Gi =a+ PEi

Only accept sessions where 1h < p < 2




Scoring: refinements

• There may be an unknown time-offset - Traffic takes time to relay through the TOR network - SIGINT clocks may not be synchronised - We slide the traces against each other and find the best

match - Truncate to exit node trace (we know that it is a

complete TOR circuit)

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Self-comparison beta rA2

-500 0 500

• We show how the score 2 .0 CtoS 1 StoC

1.5

1

behaviour as a function 1.0

0 .5

of time slide 0 .0 ~ /~

CtoS 2a StoC 2a

• See high correlation fLo u (pink) at small time 2.0

1.5

CtoS 2b StoC 2b

offset 1.0

0 .5

0.0 ~ A CtoS 3 StoC 3

• Also generally see ~ (blue) in a sensible A ~

CtoS 4 StoC 4

range 2.0

1.5

1.0

0 .5

0.0 ~ ~ -500 0 500

Time offset Is



2 .0

1.5

1.0

0 .5

0 .0

2.0

1.5

1.0

0.5

0.0


False positives

• Want an algorithm with very low false positive rate • Used 2 hours of (timestamp, source IP, destination

IP) tuples captured from 4 lOG internet bearers • Filtered to tuples between a guard node and a non

TOR node • Allow time to arbitrarily slide +/- 2 hours

- In real redeployment one would restrict this slide

• Allow us to plot ROC curves for the technique



UK TOP SECRET STRAF

False positives

• Linear- log ROC curve plot • Server-to-client good

We miss the very short "2a" session with no false-positives Threshold r2=0.998

• High as comparing increasing functions

• Client-to-server direction -many false positives

There's less structure in data as less data flows in this direction when web-browsing

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~ .,....

ro 0

2 !'!:!

(£)

~ 0

'iii 0 0.. """ 0 Q) ::::l .=

N 0

0 0

0

oO 0

Q)

-ro ..... (£)

~ 0 :;:::; 'iii 0

""" 0.. Q) 0 ::::l .=

N 0

0 0

Server to client

-

-

-

-

-

-I I I I

1e-06 1e-04 1e-02 1e+OO

False positive rate

Client to server

1e-06 1e-04 1e-02 1e+OO

False positive rate


A larger experiment

• We want to find some false hits to understand worst case accuracy for the server-to-client direction

• Let's open the aperture very wide - 2027 bearer hours of logs with any time slide - Filter to all traffic involving a TOR node

• Not just likely guard-to-client traffic as before

• We find some false hits (540) but rate is assessed to be low enough.

• 92% of false hits are against the big download session which has little structure




The next step

• We are collecting the required logs of packet times with TOR guard nodes in SIGINT

• GTE I JTRIG have adapted some TOR exit nodes we own to collect the required exit node data - We are keen to engage with others with exit nodes too

• Then run the attack - Expect to basically work

- Some extra work might be required to only allow queries on sessions with enough structure

• Need the bulk data first to progress this question

~ ~ ~ This information is exempt from disclosure under the Freedom of I i ~G Q~ other UK information legislation. Refer disclosure requests to GCHQ



R package

e can be downloaded from

• Includes algorithm and the collected web-browsing data

• Recommend R packages for sharing analytics, can contain: - R I C I Fortran code - Example data - Runnable examples and documentation - Unit tests




Conclusion

• Have shown a potential externals-based deanonymisation attack for TOR - Requires SIGINT collection of guard-to-client packet

times - Requires TOR collection from exit nodes we own

• Hope to get this running live at GCHQ soon

• Full paper and software available from




Questions?

• Work by •



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