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REPUTATION MANAGEMENT IN DECENTRALIZED NETWORKS

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Centralized systems web marketplaces, e.g. eBay. Decentralized systems ... Avoid arithmetic summation schemes: eBay. Reputation fading: PeerTrust ... – PowerPoint PPT presentation

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Title: REPUTATION MANAGEMENT IN DECENTRALIZED NETWORKS


1
REPUTATION MANAGEMENT IN DECENTRALIZED NETWORKS
  • MAJOR AREA EXAMINATION
  • GAYATRI SWAMYNATHAN
  • Committee Dr. Kevin Almeroth (chair), Dr. Ben
    Zhao, Dr. Rich Wolski
  • March 9th, 2005

2
Electronic communities
  • Growing popularity of electronic communities
  • Centralized systems web marketplaces, e.g. eBay
  • Decentralized systems
  • P2P file sharing systems

3
Decentralized Systems
  • An environment offering opportunities and threats
  • System is vulnerable to attacks from greedy and
    malicious peers
  • Distrust runs high!

4
Major Area Focus
  • Need for trust mechanisms
  • To assess trustworthiness of peers and the
    content
  • To deter malicious behavior
  • Use of reputation to build trust
  • By content assurance and peer reliability,
    reputation systems help secure decentralized
    networks

5
Outline
  • Background
  • Reputation management
  • Framework
  • Design aspects and related research
  • Future directions

6
Outline
  • Background
  • The role of reputation
  • A reputation system
  • Reputation management
  • Framework
  • Design aspects and related research
  • Future directions

7
The Role of Reputation
  • Real world transactions personal and corporate
    reputations
  • Reputation is an assumption that past behavior is
    indicative of future behavior
  • Higher the online reputation the more
    trustworthy the entity
  • eBays Feedback Forum1

1Source eBay. ebay home page, http//www.ebay.com
, 2005.
8
A Reputation System
  • Helps establish mutual trust (distrust) by
    assigning a reputation to each peer
  • How? Aggregate, process and disseminate
    transaction-based feedback
  • Challenges1 of a reputation system
  • Provide information that allows peers to
    distinguish between trustworthy and
    non-trustworthy peers
  • Encourage peers to be trustworthy
  • Discourage participation from those who are not

1Source P. Resnick, K. Kuwabara, R. Zeckhauser,
and E. Friedman. Reputation systems.
Communications of the ACM, 2000.
9
Outline
  • Background
  • Reputation management
  • Framework
  • Design aspects and related research
  • Future directions

10
Outline
  • Background
  • Reputation management
  • Framework
  • Design aspects and related research
  • Future directions

11
Reputation Management Framework
  • Generation The production of reputation
  • Modeling The reputation-based trust model
  • Storage The storage of reputation data
  • Communication The reputation exchange protocol
  • Security Safeguarding reputation from attacks

12
Reputation Management
  • Generation The production of reputation
  • Who generates reputation? How is it generated?
    What is the context of reputation?

13
Reputation Management
  • Generation The production of reputation
  • Modeling The reputation-based trust model
  • What is the trust model? How are individual
    ratings converted to a reputation profile? Are
    there feedback incentives?

14
Reputation Management
  • Generation The production of reputation
  • Modeling The reputation-based trust model
  • Storage The storage of reputation data
  • How is reputation data stored? What is stored?
    Where is it stored?

15
Reputation Management
  • Generation The production of reputation
  • Modeling The reputation-based trust model
  • Storage The storage of reputation data
  • Communication The reputation exchange protocol
  • How is reputation information exchanged? What
    parties are involved? What is transferred?

16
Reputation Management
  • Generation The production of reputation
  • Modeling The reputation-based trust model
  • Storage The storage of reputation data
  • Communication The reputation exchange protocol
  • Security Safeguarding reputation from attacks
  • What are the security threats? How to protect
    the system from unfair ratings, and colluding
    parties? Is data integrity assured?

17
Reputation Management Framework
18
Outline
  • Background
  • Reputation management
  • Framework
  • Design aspects and related research
  • Future directions

19
Reputation Management Generation
20
Generation Design Aspect
  • A reputation is generated by participants
    undertaking a transaction.
  • Context of reputation file, peer, etc.
  • Participants and roles

Reputation seeker
Reputation holder
Reputation evaluator
Service requester
Service provider
21
Generation Design Aspect
  • Participants and behavior
  • Honest
  • Dishonest
  • Dynamic personality

22
Generation Approaches
  • Feedback
  • Rating scales 0-10, Good, Ok, Bad
  • Context of reputation
  • Peer-based PeerTrust1, PRIDE, etc.
  • Resource-based
  • Peer and resource-based XRep2

1 Source L. Xiong and L. Liu. Peertrust
Supporting reputation-based trust for P2P
electronic communities. IEEE Trans. On KDE,
2004. 2 E. Damiani, et al. A reputation-based
approach for choosing reliable resources in P2P
networks. In Proc. of the ACM CCS, 2002.
23
Generation Approaches
  • XRep1 combines peer-based and file-based
    reputations
  • Advantages of file-based reputations
  • Avoid cold start problem for newcomers
  • Load balancing
  • More persistent
  • Advantages of peer-based reputations
  • Blacklisting peers
  • Avoid cold start for files

1 Source E. Damiani, D. C. di Vimercati, S.
Paraboschi, P. Samarati, and F. Violante. A
reputation-based approach for choosing reliable
resources in peer-to-peer networks. In Proc. of
the ACM CCS, 2002.
24
Reputation Management Modeling
25
Modeling Design Aspect
  • Feedback
  • Number of transactions
  • Credibility of feedback
  • Transaction context factor
  • Size
  • Time
  • Incentive schemes

26
Modeling Approaches
  • Modeling direct and indirect observations A - B
    - C so A-C
  • Correlated trust Managing Trust, OpenPrivacy,
    EigenTrust
  • Separate trust metric PeerTrust

27
Modeling Approaches
  • Managing Trust1
  • Complaints-based model
  • Not robust to varying personalities of peers

1Source K. Aberer and Z. Despotovic. Managing
trust in a Peer-2-Peer information system. In
Proc. of the CIKM,2001
28
Modeling Approaches
  • Managing Trust1
  • Complaints-based model
  • Not robust to varying personalities of peers
  • OpenPrivacy2
  • Web-of-trust style network of peer certificates
  • Certificate rating, confidence value
  • Node distance distrust table

1Source K. Aberer and Z. Despotovic. Managing
trust in a Peer-2-Peer information system. In
Proc. of the CIKM,2001 2 K.Burton. Design of the
openprivacy distributed reputation system.
http//www.openprivacy.org, 2002
29
Modeling Approaches
  • EigenTrust1
  • A trusts B, B trusts C A trusts C
  • Matrix of normalized local trust and global trust
    values

1 Source S. Kamvar, M. Schlosser, and H.
Garcia-Molina. The eigentrust algorithm for
reputation management in P2P networks. In Proc.
of the Intl. WWW conference,2003.
30
Modeling Approaches
  • EigenTrust1
  • A trusts B, B trusts C A trusts C
  • Matrix of normalized local trust and global trust
    values
  • PeerTrust2
  • Three basic parameters
  • Feedback, number of transactions, credibility of
    feedback
  • Two adaptive parameters
  • Transaction context
  • Community context
  • Separate trust metric defined for credibility of
    feedback

1 Source S. Kamvar, M. Schlosser, and H.
Garcia-Molina. The eigentrust algorithm for
reputation management in P2P networks, 2003. 2
L. Xiong and L. Liu. Peertrust Supporting
reputation-based trust for P2P electronic
communities. IEEE Trans. On KDE, 2004.
31
Reputation Management Storage
32
Storage Approaches
  • DHT-based approach
  • Each peer holds trust data for multiple peers,
    and routing table
  • PeerTrust, EigenTrust, Managing Trust
  • Data integrity redundancy, anonymity, digital
    signatures
  • Unstructured storage approach
  • Certificates OpenPrivacy, RCertPX1
  • Experience Repository XRep
  • Data integrity digital signatures

1 Source B. Ooi, C. Liau, and K. Tan. Managing
trust in peer-to-peer systems using
reputation-based techniques. In WAIM, 2003.
33
Reputation Management Communication
34
Communication Approaches
  • DHT-based approaches
  • PeerTrust, EigenTrust, Managing Trust
  • Search and update using query or insert messages
  • Exploit communication protocol of base network
  • XRep Vote polling via broadcast
  • Poll messages implemented on top of Query
    messages
  • Specific exchange protocols
  • OpenPrivacy Repute exchange protocol (REP)

35
Reputation Management Security
36
Reputation Management Security
37
Security Challenges and Approaches
  • The problem of dynamic peer personalities
  • Avoid arithmetic summation schemes eBay
  • Reputation fading PeerTrust
  • The problem of unfair ratings
  • Credibility of feedback PeerTrust
  • The problem of liar farms
  • PRIDE IP-based safeguard

1 Source P. Dewan and P. Dasgupta. Pride
peer-to-peer reputation infrastructure for
decentralized environments. In WWW 2004.3737
38
Security Challenges and Approaches
  • The problem of collusion (bad mouthing and ballot
    stuffing)
  • EigenTrust Use of pre-trusted peers
  • PeerTrust Feedback similarity function
  • Storage integrity
  • Exchange integrity

39
Reputation Systems
EigenTrust PeerTrust PRIDE
RCert EigenTrust PeerTrust
Storage
Security
Generation
XRep
Communication
Modeling
EigenTrust OpenPrivacy
PeerTrust EigenTrust
Reputation System
Decentralized System
40
State of Current Research
  • Not deployed!
  • One or two design aspects considered
  • Not scalable
  • Portability not considered
  • Security loopholes

41
Outline
  • Background
  • Reputation management
  • Framework
  • Design aspects and related research
  • Future directions

42
Future Directions
  • To build a reputation system that is
  • Scalable and robust
  • Generic system not application specific
  • Flexible trust model
  • Easily deployable

43
Conclusions
  • Reputation-based trust mechanisms help establish
    trustworthiness of peers
  • Different reputation models to detect and isolate
    malicious behavior in decentralized systems
  • State of current research
  • Some future directions

44
Questions?!
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