1. The EigenTrust Algorithm for Reputation Management in P2P Networks
Sepandar D.Kamvar Mario T.Schlosser Hector Garcia-Molina
Presenter: Jianming Zhou

2. Problem Problem in P2P: Objective: Basic Idea
Inauthentic files distributed by malicious nodes
Objective:
Identify the source of inauthentic files and bias against downloading from them
Basic Idea
Reputation System:
Assign a trust value to each peer on its previous behaviors

3. Challenges Need an distributed reputation system Desired features
Success like C/S reputation system (eg. eBay)
Provide comprehensive evaluation of peer
Lower overhead
Desired features
Self-policy, i.e., no central server
Maintain anonymity
Robust to malicious node and sybil attack
Minimal overhead

4. EigenTrust -- Intro Basic idea Terminology
Each peer has a Global Reputation given by the local trust values assigned by other peers
Terminology
Local trust value: cij
The opinion peer i has of peer j, based on past exp.
Each time peer i downloads an authentic/inauthentic file from peer j, cij increases/decreases.
Global trust value: ti
The trust that the entire system places in peer i

5. More about Local trust value
Normalization
Otherwise, malicious peers can assign arbitrarily high local trust value to other malicious peers
All cij is non-negative
ci1+ci2+ci3+…+cin = 1
Local Trust Vector: ci
contains all local trust values cij that peer i has of other peers j

6. Other Approaches Foundation of EigenTrust Past Experience
Reply on past experience
Friend-friend reference
Past Experience
Each peer bias choice based on its vector ci
Peer with good experience will likely be selected
Problem: each peer has limited past experience, knowing few other peers
Ask friend opinion of other peers
Weight their opinion by your trust in them
Problem: various number of friends for each peer
What their opinion of peer k
Ask friend j
Weight your friend’s opinion by how much you trust them

7. EigenTrust Combine and enhance Comprehensive
Comprehensive, i.e., knowing all peers
Lower overhead in term of computation and storage
Comprehensive
Iterative friend-friend reference
Ask your friend:
Ask their friend:
Ask until all nodes:
N large, converge to same vector for every peer i
Peers can cooperate to compute and store t

8. Basic Algorithm:non-distributed
Initialize
Repeat until converge

9. Distributed algorithm 1
Each peer store its local trust vector
Each peer store its own global trust value
Each peer compute its own ti
The component-wise version of
is the distribution over pre-trusted peers
Anti- malicious collectives and guarantee converge

10. Distributed algorithm 2
For each peer i {
-First, ask peers who know you for
their opinions of you.
-Repeat until convergence {
-Compute current trust value:
ti (k+1) = c1i t1(k) +…+ cni tn(k)
-Send your opinion cij and trust value ti(k)
to your acquaintances.
-Wait for the peers who know you
to send you their trust values and opinions. }

11. Secure EigenTrust Peer should not hold its own t
Problem: malicious node can report false value
Solution: different peer compute t for one peer
Leverage DHT
T should not be computed by only one peer
Problem: malicious node can collude
Solution: multiple score managers + majority rule
Score manager: peer i is j’s score manager if i computes its global trust value

12. Usage of global trust value
Isolating malicious nodes
bias the download from more reputable nodes
Potential problem: highly trusted node overloaded
Incenting freeriders to share
Hinder the spread of inauthentic files

13. Performance Setup Node selection in trust system
Deterministic algorithm => overload
Probabilistic algorithm => balanced

14. Performance Thread Model A:Individual Malicious Peers
B:Malicious Collectives
C:Malicious Collectives with Camoflouge
D:Malicious Spies

15. Thread model A:

16. Thread model: B

17. Thread model: C

18. Thread model: D

19. Conclusion EigenTrust
Dramatically reduces number of inauthentic files on the network.
Robust to malicious peers.
Low overhead

20. Q&A