1. Cope with selfish and malicious nodes
Jinyang Li

2. P2P requires cooperation
Cooperation means nodes obey design
However, P2P users control the nodes
Modify the given software
Shut down application
Delete app files
Rate limit application etc.
P2P users are mostly selfish
Avoid contributing resources as much as possible
P2P nodes could be malicious
Adversary can enroll (arbitrarily) many nodes
P2P nodes speak the “right” protocol,
but might not do the “right” things.

3. What if anyone can run Coral?

4. Design space for combating misbehaving nodes
Enforce nodes to run desired software
Obfuscate protocol/software
Rely on hardware support to authenticate a running piece of software (Trusted computing)

5. Design space for combating misbehaving nodes
2. Encourage nodes not to be selfish
Design protocols so it is in a node’s best interest to contribute
3. Choose trustworthy nodes for interaction
If only a few trusted nodes turn out to be bad, it is okay since data/service is replicated

6. #2 Encourage non-selfish behavior
What do selfish users do in file-sharing?
Download from others, but refuse to upload
Why is it bad?
If everybody behaves like this, system is useless

7. A layman’s view of game theoryC
Global optimal:
Requires both to cooperate D
3,3
0,5
5,0
1,1 C
Nash equilibrium
both defect,
worst global outcome D
Prisoner’s dilemma (PD)

8. Tit-for-tat What if boy and dog play the game over many iterations?
Cooperate in the 1st round, mirror what your opponent did in the last round
Tit-for-tat with forgiveness:
Occasionally cooperate to end a streak of retaliation and counter-retaliation

9. Tit-for-tat for file sharing
Exchanging data between peers is like an iterated PD game
Break data exchange in multiple rounds.
If remote peer does not upload fast enough (defect), choke his download (play defect).

10. Bittorrent Group all peers interested in the same file into a swarm
Each node has sth. the other wants
A big file is broken into pieces
Each node downloads pieces in random order
Every 10 seconds, calculate a remote peer’s upload rate, if no good, choke it
Tit-for-tat
Periodically chooses one random peer to unchoke
…with forgiveness

11. How tit-for-tat helps BT
Tit-for-tat in BT ensures fair exchange(?)
Tit-for-tat prevents selfish behavior(?)
All selfish behaviors are non-profitable(?)

12. Cautions in applying tit-for-tat in other scenarios
The game must be played over many rounds
Each peer must have “goods” valued equally by the other
What’s at stake?

13. # Combating malicious nodes
Malicious (Byzantine) nodes
Their goal is to bring max harm to you
May also behave randomly and unpredictably
Basic strategy
replicate data/functionalities
Obtain data or votes of results from multiple replicas
The impossibility results:
No availability when all nodes are Byzantine.
No correct agreement when >1/3 nodes are Byzantine.

14. What’s at stake? What does the system vote on?
launch a nuclear missile
Buyer or seller’s reputation (eBay)
Importance of a webpage (Google)
Interesting news (digg)
Authenticity of a shared file (Credence)

15. Who can vote? eBay, digg: any registered users
Can an adversary register millions of users?
Must ensure votes come from independent parties
Restrict voters to humans
Restrict one identity per human
Credence:
Central authority issues public key to nodes
Limit how fast keys are issued to each node

16. What to vote on? Votes could be on subjective or objective matters
(Digg) Interesting vs. boring news
Credence insight:
Make votes objective, honest users  similar votes
Example votes:
<abf3: britney  name, mp3 = type>K
<ba9f: britney  name, mp3  type>K
<35e4: name = >K
Binds a vote to its file
Binds a vote to a user

17. How to cast votes?
U1 downloads files abf3,ba9f,35e4 with search term “britney mp3”
<abf3: britney  name, mp3 = type>K
<ba9f: britney  name, mp3  type>K
<35e4: name = >K

18. How to use votes?
U2 obtains hash abf3,ba9f,35e4 from search “britney mp3”
Goal: Rank hashes according to votes
Collect a list of votes for each hash from peers
Weight peers using voting history correlation
Compute weighted aggregate votes on each hash
Sort

19. Weight peers based on vote correlation
My votes
U1’s votes
abcd britney  name,
b234 spears  name,
4567 madonna  name
ff45 nina  name
1234 britney  name
abf3 britney  name
b234 britney  name
4567 madonna  name
ff45 nina  name
1234 britney  name
4 votes on same files; 2 positive agreements
P=.5
2 positive votes from me, 3 positive votes from U1
a=.5, b=.75
Correlation (p-ab)/sqrt(a(1-a)b(1-b)) = 1.36

20. Weight peers based on vote correlation
My votes
U2’s votes
abcd britney  name,
b234 spears  name,
4567 madonna  name
ff45 nina  name
1234 britney  name
abf3 britney  name
b234 britney  name
4567 madonna  name
ff45 nina  name
1234 britney  name
4 votes on same files; 1 positive agreements
P=0.25
2 positive votes from me, 3 positive votes from U1
a=.5, b=.75
Correlation (p-ab)/sqrt(a(1-a)b(1-b)) = -0.57

21. What if there are no overlapping files?
Use transitive correlation
If A has high correlation with B, B has high correlation with C, then A has high correlation with C

22. Summary on DHT and P2P
What did you learn?