1. Re3 : Relay Reliability Reputation for Anonymity Systems
Anupam Das (UIUC),
Nikita Borisov (UIUC),
Prateek Mittal (Princeton University)
Matthew Caesar (UIUC) 1
November 21, 2018November 21, 2018

2. Anonymity System
Hides user identity and defends users against internet surveillance and traffic analysis. Tor is a system that provides online anonymity.
~5000 Tor Relays
~300,000 Users daily 2
November 21, 2018November 21, 2018

3. How Tor Works? M M M M
Exit
Tor Relay
Encrypted link
Unencrypted
link
Guard
Middle
Guards:
Defend from the predecessor attack
By default 3 guards per user
Tor circuit /tunnel is built incrementally one hop by one hop
Layered encryption is used
Each router knows only its predecessor and successor 3
November 21, 2018November 21, 2018

4. End-to-end Timing Attack in Tor
Tor relays are run by volunteers. So relays can be malicious.
Timing Correlation
Assuming c fraction of the total bandwidth is controlled by an adversary and g fraction of the guards (per user) are compromised,
Probability of circuits being compromised: 4
November 21, 2018November 21, 2018

5. Attack Amplification via Selective DoS
New Circuit
Dropped
Not Dropped
C- Compromised
H- Honest Relay
Guard
Middle
Exit H C
Guard
Middle
Exit C H
Dropped 5
November 21, 2018November 21, 2018

6. Impact of Selective DoS
Under Normal Condition:
Under Selective DoS:
Guard
Middle
Exit C H
For any given value of g,c>0 we have, 6
November 21, 2018November 21, 2018

7. Recent Attacks on Tor
Some law-enforcement officers and researchers say the shakiness of the network itself, which relies on volunteers, presents opportunities for authorities to trace users
It would allow Dutch police to use exploits and malware against privacy systems like the Tor network
In his , Snowden wrote that he personally ran one of the “major Tor exits”–a 2 gbps server named “TheSignal”–and was trying to persuade some unnamed coworkers at his office to set up additional servers. 7
November 21, 2018November 21, 2018

8. Our Goals
Capture circuit dropping characteristics of relays using a localized reputation framework.
Adaptively penalize relays exhibiting frequent behavioral oscillation.
Filter potentially compromised/unreliable relays.
Threat Model:
Small fraction (~20%) of relays are compromised.
Compromised relays strategically drop circuits. 8
November 21, 2018November 21, 2018

9. Adaptive Reputation Metric
Goals:
Effectively summarize historical behavior
Use an Exponentially Weighted Moving Average
Discourage behavioral oscillation
Dynamically adjust the weight of the EWMA
(Impact of sudden drop > Impact of sudden rise) X Y Z
Node
Rep
New
Exp X Rx Fx Y Ry Fy Z Rz Fz
Node
NewError
Acc
Error X δx εx Y δy εy Z δz εz
Node
Rep X Rx Y Ry Z Rz
Node
Rep X
EWMA(Rx, Fx)=Rx Y
EWMA(Ry, Fy)=Ry Z
EWMA(Rz, Fz)=Rz
New Feedback
Update weight
of the EWMA
Computer Errors 9
November 21, 2018November 21, 2018

10. Closer Look at Reputation Metric
Reaction to random network failures or strategic oscillating behavior-
50% random drop
50% oscillating behavior
Circuit dropping results in lowering reputation. Strategic oscillating behavior is punished more severely and this is evident from the lower reputation score for the same drop rate. 10
November 21, 2018November 21, 2018

11. Confidence Factor
To hinder whitewashing attack we associate a confidence factor to each relay’s reputation score.
𝐶𝑜𝑓 𝑛 (𝑥)= β 1/𝑛
where, 0< β <1
Monotonically increasing function of the number of interactions with a given relay
Final Ranking Score for a relay:
𝑅𝑎𝑛𝑘 𝑛 𝑥 = 𝑅𝑒𝑝 𝑛 𝑥 · 𝐶𝑜𝑓 𝑛 (𝑥) 11
November 21, 2018November 21, 2018

12. Relays sorted in descending order of ranking score
Filtering Protocol
Relays sorted in descending order of ranking score
1-γ γ
Consider only top (1-γ) fraction of the relays
Top (1-γ) ranked relays
Compute : Mean (μ) , Standard Deviation (σ)
Filter Relays with |Rank-μ| > k·σ
If compromised guards >1, compromised exits obtain higher reputation score so consider filtering on both sides
+ k·σ μ
- k·σ
For guards we investigate the following two strategies:
Strategy 1: Consider all guards that are not outliers.
Strategy 2: Consider only the highest ranked guard. 12
November 21, 2018November 21, 2018

13. Attack Scenarios
We probabilistically analysis the following attack scenarios:
Attack
Description
Example
[Guard-Middle-Exit]
Allowed
Dropped
Selective DoS
Drop all non-compromised circuits
C - H - C
H - C - H
Random Dropping
Randomly drop a non-compromised circuit (with various drop rate)
[H - C - H]
H - C – H
Targeted Attack
Drop circuit if a target relay lies on the circuit
H - C - T
Creeping Death
Drop circuit if majority of the relays are honest
H - C - C
C : compromised relay, H: honest relay, T: targeted relay 13
November 21, 2018November 21, 2018

14. Evaluation Simulation setup:
We perform both simulations and real world experiments.
Simulation setup:
Gather live Tor relay information (IP, Bandwidth, Selection probabilities) from
Randomly assigned 20% bandwidth to be compromised.
Parameter
Description
Value/Range
Computational
𝐾 𝑝
Proportional gain
0.5 μ
Rewarding factor 2 ν
Punishment factor 1 β
Confidence Co-efficient
Environmental g
Fraction of malicious guard
{0,1/3,2/3,1} d
Drop rate by malicious relays
[0,1] f
Transient Network failure
0.21
To approximate the failure rate present in the current Tor network we use TorFlow project
We generate 10,000 Tor circuits and record their failure rate. Average failure rate after 10 run was found to be
approximately 21%.
Parameters are set after performing parameter sensitivity
Transient network failure computed using TorFlow project 14
November 21, 2018November 21, 2018

15. Filtering Malicious Relays
With g=1/3 we can filter malicious relays efficiently.
Even with g=2/3 we can filter significant portion of the malicious relays.
Majority of the relays are honest (~80%)
So μ and σ are more influenced by honest relays 15
November 21, 2018November 21, 2018

16. False Errors
False Negative (FN)= Fraction of compromised relays accepted
False Positive (FP)= Fraction of honest relays discarded
Ideally we want both FN and FP as small as possible.
As nodes start misbehaving more, FP and FN rates fall 16
November 21, 2018November 21, 2018

17. Selecting Compromised Circuits
Probability of selecting a compromised circuit after filtering:
Pr⁡(𝐶𝑋𝐶)= 𝑔 𝑓∙ 𝑐 𝑓 𝑔 𝑓∙ 𝑐 𝑓 + 1− 𝑔 𝑓 1− 𝑐 𝑓 −𝑑 [1− 𝑔 𝑓∙ 𝑐 𝑓 − 1− 𝑔 𝑓 1− 𝑐 𝑓 2 ]
In our approach for g<1, the attacker has best results with no drops 17
November 21, 2018November 21, 2018

18. Strategic Dropping
The adversary adopts the following strategy- “Drop circuit only if its reputation is above a chosen threshold”
To obtain a positive reputation score the adversary cannot afford to drop too many circuits.
The probability of constructing a compromised circuit (Pr(CXC)) reaches to a stable value as drop rate declines to zero. 18
November 21, 2018November 21, 2018

19. Real World Experiments
We use Emulab and PlanetLab machines for our experimental setup.
Tor Network
Destinations
Our Traffic Analyzing Server
Our relays
Timing info
sent to server
PlanetLab Clients
11 Emulab machines= 10 run Tor protocol (20Kbps)+1 acted as server (gathering timing info from the other 10 machines) [Bauer et al. WPES 07]
Used 39 regular Tor node and added our 10 compromised nodes (c≈20%). 19
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20. Results From Live Tor Network
We use PlanetLab machines to emulate users from five different continents. User traffic is emulated by retrieving a random web file of 300 KB in size.
Similar to our simulations we see that as the number of compromised guards increases, FN also increases 20
November 21, 2018November 21, 2018

21. Measuring Relay Reliability
We look at network-level (probing Tor ORport using nmap) and application-level (creating Tor circuits) reliability.
Significant deviation in application and network level reliability. Certain fraction of the Tor relays drop circuits more often than others even though they are reachable. 21
November 21, 2018November 21, 2018

22. Predicting Relay Reliability
The correlation between the advertised bandwidth and reliability < So, bandwidth is not an indicator of reliability in Tor network.
We also verified that past performance is an indication of future results. We found the “Pearson Correlation” to be 0.72
Testing Reliability on the live Tor network 22
November 21, 2018November 21, 2018

23. With 1000 interactions we can profile ~600 relays
Deployment Strategies
We propose 2 ways to deploying Re3 into the Tor network:
Localized: Individual Tor clients run Re3
Centralized: Re3 is run by Directory Authorities (DA)
With 1000 interactions we can profile ~600 relays 23
November 21, 2018November 21, 2018

24. Conclusion Our work shows:
You can profile the reliability of Tor relays through a reputation framework.
Reliability reputation coupled with a filtering protocol can successfully filter compromised/unreliable relays.
In the absence of attacks profiling relay reliability can significantly improve the reliability of Tor circuit construction. 24
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25. End 25
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