Market transactions are subject to information asymmetry about the delivered value proposition, causing transaction costs and adverse market effects among buyers and sellers. Information systems research has investigated how review systems can reduce information asymmetry in business-to-consumer markets. However, these systems cannot be readily applied to business-to-business markets, are vulnerable to manipulation, and suffer from conceptual weak spots since they use textual data or star ratings. Building on design science research, we conceptualize a new class of reputation systems based on monetary-based payments as quantitative ratings for each transaction stored on a blockchain. Using cryptography, we show that our system assures content confidentiality so that buyers can share and sell their ratings selectively, establishing a reputation ecosystem. Our prescriptive insights advance the design of reputation systems and offer new paths to understanding the antecedents, dynamics, and consequences to reduce information asymmetry in B2B transactions.

In this paper, 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.

We present CLARC (Cryptographic Library for Anonymous Reputation and Credentials), an anonymous credentials system (ACS) combined with an anonymous reputation system. Using CLARC, users can receive attribute-based credentials from issuers. They can efficiently prove that their credentials satisfy complex (access) policies in a privacy-preserving way. This implements anonymous access control with complex policies. Furthermore, CLARC is the first ACS that is combined with an anonymous reputation system where users can anonymously rate services. A user who gets access to a service via a credential, also anonymously receives a review token to rate the service. If a user creates more than a single rating, this can be detected by anyone, preventing users from spamming ratings to sway public opinion. To evaluate feasibility of our construction, we present an open-source prototype implementation.

In this paper, we introduce the notion of delegatable attribute-based anonymous credentials (DAAC). Such systems offer fine-grained anonymous access control and they give the credential holder the ability to issue more restricted credentials to other users. In our model, credentials are parameterized with attributes that (1) express what the credential holder himself has been certified and (2) define which attributes he may issue to others. Furthermore, we present a practical construction of DAAC. For this construction, we deviate from the usual approach of embedding a certificate chain in the credential. Instead, we introduce a novel approach for which we identify a new primitive we call dynamically malleable signatures (DMS) as the main ingredient. This primitive may be of independent interest. We also give a first instantiation of DMS with efficient protocols.