1. Detecting Bad Mouthing Behavior in Reputation Systems
Kuan-Ta Chen (Chun-Yang Chen) , Cheng-Chun Lou , Polly Huang , and Ling-Jyh Chen
1 2 2 1
1
Academia Sinica, 2National Taiwan University
Background Hypothesis Votee-Voter-based Collusion Cluster Detection
• MMORPGs (Massively Multiplayer Online Role-Playing Games) • The most voters of legitimate players are likely collusion cluster The relationship of victim group is stronger than random votee cluster
have become extremely popular • In case if a collusion cluster attacks for several times
First take the votees with more common voters
1. Collusion Cluster has more common votees than random
• form the victim group
• Game bots voter cluster
○ Auto-playing game clients 2. Victims have more common voters than random votee cluster Then take union of the voters of the victim group
○ One of the greatest threats of MMORPGs • form the collusion cluster candidate
• Based-on Apply Voter-based Collusion Cluster Detection
• Detection of Game Bots ○ The voters & votees id of each player
○ Manual detection (game master) [1] • Note
○ Traffic analysis approach [2] ○ When not attack, a collusive player acts as a legitimate player Performance Evaluation Results
○ Voting-based system [3] Voter-Based Votee-Voter-Based Comparison
- Each player votes the suspicious player as a game bot Voter-Based Collusion Cluster Detection # of Attack
(Single CC or Multiple CC)
More attacks  higher accuracy Votee-Voter > Voter
The relationship of collusion cluster is stronger than random voter cluster No influence Need more than 3
Motivation Take the voters with more common votees between each other
Collusion Cluster Size
high accuracy high accuracy
Voter > Votee-Voter
Prob. of Collusive Player
• form the collusion cluster. Attack Vote
Higher Prob.  higher accuracy Votee-Voter > Voter
• Problem in voting-based system
General Case Malicious Case 3 ID Votee List
4
1 1 11, 12, 13, 14, 17 Voter-Based scheme:
5
4 2
2 11, 12, 13, 14, 15, 18 Robust to the size of collusion cluster
1 4 3 9, 13, 14, 15
4 3 3
4 11, 12, 13, 14 Voter-Votee-Based scheme:
BOT
BOT
1 Robust to the number of attacks
BO
BO
BO
BO 2 4 1 5 12, 13, 14, 15, 25, 60
1
T T
T T
2 1 9 17, 25, 30
BO T B OT
1
3
3
18
10 17, 18, 50, 56 Conclusion
10 11 17, 18, 70, 44 • Two mechanisms to detect the collusion cluster
BOT User
1 1
12 17, 20, 35 ○ Based on the voting history
1
• Collusion 13
13 40, 45, 50 ○ Single cluster or multiple clusters
1 14 55, 80, 90
○ A secret agreement between two or more parties for a fraudulent,
17
9
1
illegal, or deceitful purpose [4] 1 1
15 20, 30, 40 • Accuracy
- Unfairly low ratings – bad mouthing
14
1 1
17 1 ○ Attack more than three times: 83%+
1
- Unfairly high ratings – ballot stuffing 18 17, 60 ○ Attack more than five times: 97%+
15 1 12
11 Weight (A, B): # of common
• Only can vote negatively (game bot) 1 votees of A and B • Adjust other experimental factors
○ Only collusion cluster size and prob. of collusive player attack vote
○ This study focuses on bad-mouthing attacks < Algorithm >
have the obvious influence to the accuracy
while ( edge(G ) ∉ Φ )
Problem Formulation Take the edge with the largest weight
• Bad-Mouthing
while (not termination condition ) Furture Work
Take the outlier edge with the largest weight Detecting players who participate in multiple collusion clusters
○ A malicious group deliberately vote a legitimate player as a end while
game bot output [1] I. MacInnes and L. Hu, “Business models and operational issues in the chinese online game
• Terms end while industry,” Telematics and Informatics, vol. 24, no. 2, pp. 130-144, 2007
○ Collusion Cluster: a bad-mouthing group [2] K.-T. Chen, J.-W. Jiang, P. Huang, H.-H. Chu, C.-L. Lei, and W.-C. Chen, “Identifying mmor-
Terminal Condition:
○ Victim: the legitimate players who are under bad-mouthing attacks ∑{weight (u,v) | u, v ⊂ S ' } − ∑{weight (u,v) | u, v ⊂ S} < a pg bots: A traffic analysis approach,” in Proceedings of ACM SIGCHI ACE, 2006
• Goal S [3] Blizzard, http://www.blizzard.com/war3/
To Detect the Collusion Clusters [4] http://www.answers.com/collusion?cat=biz-fin