Incentive systems (such as customer loyalty systems) are omnipresent nowadays and deployed in several areas such as retail, travel, and financial services. Despite the benefits for customers and companies, this involves large amounts of sensitive data being transferred and analyzed. These concerns initiated research on privacy-preserving incentive systems, where users register with a provider and are then able to privately earn and spend incentive points.

We introduce updatable anonymous credential systems (UACS) and use them to construct a new privacy-preserving incentive system. In a UACS, a user holding a credential certifying some attributes can interact with the corresponding issuer to update his attributes. During this, the issuer knows which update function is run, but does not learn the user's previous attributes. Hence the update process preserves anonymity of the user. One example for a class of update functions are additive updates of integer attributes, where the issuer increments an unknown integer attribute value v by some known value k. This kind of update is motivated by an application of UACS to incentive systems. Users in an incentive system can anonymously accumulate points, e.g. in a shop at checkout, and spend them later, e.g. for a discount. In this paper, we (1) formally define UACS and their security, (2) give a generic construction for UACS supporting arbitrary update functions, and (3) construct a new incentive system using UACS that is efficient while offering offline double-spending protection and partial spending.

We present CLARC (Cryptographic Library for Anonymous Reputation and Credentials), an anonymous credentials system (ACS) combined with an anonymous reputation system.