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w
w
R
=
28
t
+
20
t
2
28,2
20,2
w
+
w
w
+
w
Peer 2
28
20
28
20
0.9
0.8
=
×
0.9
+
×
0.7
0.9
+
0.8
0.9
+
0.8
=
0.81
Aggregation
Threshold = 0.7
w
=
0.9
w
=
0.8
w
=
0.6
w
=
0.5
28
20
9
4
t
=
0.9
t
=
0.7
28,2
20,2
Peer 28
Peer 20
Peer 9
Peer 4
Qualified Peers
Disqualified Peers
FIGURE 6.9: Example of global trust aggregation [Song et al., 2005].
Distrust
Untrust
Trust
Distrust
Untrust
Trust
Undistrust
-1
0
1
-1
0
1
(a) Marsh and Dibben's definition
(b) Gri
ths et al.'s new notion
FIGURE 6.10: Notions of trust [Gri
ths et al., 2006].
proposed new notion of undistrust can generate better performance in terms
of errors in identifying malicious peers.
6.6 Game Theoretic Analysis on Trust Management
Recently, Tuan [Tuan, 2006] presented an interesting and insightful game
theoretic analysis of a general trust management system. Tuan started by
modeling the trust reporting process as a mixed strategy game [Osborne, 2004],
and found that if a reputation system is not incentive-compatible, the more
the number of peers in the system, the less likely that anyone will report about
a malicious peer.
Specifically, Tuan made use of a reasonable assumption that the cost of re-
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