1. Trusted P2P Transactions with Fuzzy Reputation Aggregation Authors: S. song, K. Hwang, and R. Zhou University of Southern California Yu-Kwong Kwok University of Hong kong Source: Internet Computing, IEEE Volume 9, Issue 6, Nov.-Dec. 2005 ppl.24 - 34 Speaker: Tzu-Hang Hsu Data: 2006/1/3

2. 2 Introduction E-commerce and online commodity exchanges Distrust among seller and buyers Often strangers to each other P2P Transaction Applications Product exchanges (sellers reputation) File-sharing applications (viruses, Trojan horses) P2P grid environment P2P:peer-to-peer

3. 3 Introduction The authors present a new P2P reputation system Based on fuzzy logic inferences Better handle uncertainty, fuzziness, and incomplete information Efficacy and robustness Testing the system using eBay transaction data P2P:peer-to-peer

4. 4 Analysis of the eBay Transaction Data Super Users versus Small Users Unstable Transactions by Small Users Skewed Transaction Amount

5. 5 FuzzyTrust System Architecture System Design Requirements – consider the unbalanced transactions among users – The super users should be updated more often than small users. – With a skewed transaction amount evaluate the large the large transaction more often then small one

6. 6 FuzzyTrust System Architecture Local-Score Computation.

7. 7 FuzzyTrust System Architecture Global Reputation Aggregation.

8. 8 FuzzyTrust System Architecture 1. If the transaction amount is very high and the transaction time is new, then the aggregation weight is very large. 2. If the transaction amount is very low or the transaction time is very old, then the aggregation weight is small.

9. 9 DHT-Based Overlay Implementation(1/2) Distributed-hash-table (DHT) – fast trust aggregation – Secure message transmission Each peer maintains two tables: – Transaction record table – Local score table

10. 10 DHT-Based Overlay network(2/2)

11. 11 Example(1/3) the system sets an aggregation threshold of 0.7

12. 12 Example(2/3)

13. 13 Example-calculate the global reputation(3/3) R i : global reputation of peer i t ji : local trust score of peer i rated by j w j : the aggregation weight of tji

14. 14 Conclusion Fuzzy logic inference is clearly effective for distributed trust management in P2P networks. Malicious Peer Detection Buyers: make late or no payments Sellers: deliver bad-quality good