This approach provides a universal framework for fraud suppression in electronic auctions.

As noted earlier, the SAM approach can combat fraud and other risks by providing a trusted place to calculate predicates on otherwise private participant information. For example:

• To prevent options front-running, the SAM can itself monitor for such correlations (without otherwise leaking bidder identity).
• To prevent money-laundering frauds, the SAM can require brokers to cryptographically commit to the identity of the end-client in each bid, at the time of the bid.
• To prevent false bids, the SAM can require some evidence of ability to pay before accepting a bid.
• To prevent rogue players from bringing down a critical infrastructure, the SAM can require some evidence of ``ability to provide service'' before accepting a seller.
• In an electronic futures market, the SAM also provides a nice place to clear orders, such as a contract-to-buy and a matching contract-to-sell.

In distributed markets (like the power grid example), these predicates can be calculated by distributed SAMs--although specifying the predicates and determining how to calculate them becomes much more interesting. Much work can be done here, depending on on the fraud and risk scenarios involved.