The EigenTrust Algorithm for Reputation Management in P2P Networks

Sepandar D.Kamvar Mario T.Schlosser Hector Garcia-Molina

Presenter: Jianming Zhou

Problem

Problem in P2P: 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

Challenges

Need an distributed reputation system 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

EigenTrust -- Intro

Basic idea 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

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

Other Approaches

Foundation of EigenTrust 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 Friend-friend reference

Ask friend opinion of other peers Weight their opinion by your trust in them Problem: various number of friends for each peer

Ask friend j What their opinion of peer k

Weight your friend’s opinion by how much you trust them

EigenTrust

Combine and enhance 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

Basic Algorithm:non-distributed

Non-distributed Initialize

Repeat until converge

T(0)t

nn

1...

1

(k)T1)(k tCt

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

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. }}

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

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

Performance

Setup Node selection in trust system

Deterministic algorithm => overload Probabilistic algorithm => balanced

Performance

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

Thread model A:

Thread model: B

Thread model: C

Thread model: D

Conclusion

EigenTrust Dramatically reduces number of inauthentic files

on the network. Robust to malicious peers. Low overhead

Q&A