  In this paper, we study methods for improving the utility and privacy of
reputation scores for online auctions, such as used in eBay, so as to reduce
the effectiveness of feedback extortion. The main ideas behind our techniques
are to use randomization and various schemes to escrow reputations scores until
appropriate external events occur. Depending on the degree of utility and
privacy needed, these external techniques could depend on the number and type
of reputation scores collected. Moreover, if additional privacy protection is
needed, then random sampling can be used with respect reputation scores in such
a way that reputation aggregates remain useful, but individual reputation
scores are probabilistically hidden from users. Finally, we show that if
privacy is also desired with respect to the the reputation aggregator, then we
can use zero-knowledge proofs for reputation comparisons.
