In client-server interaction scenarios over a network the problem of unsolicited network transactions is often encountered. In this paper, we propose a reputation model based on the behavioural history of long-lived network client identities as a solution to this problem. The reputations of clients are shared between trusted servers anonymously through global reputation analysers. Shared global reputations and local reputations help servers to infer local opinions of clients and control service levels in attempts to reduce unsolicited network transactions.