In crowdsourcing systems, requesters publish tasks, and interested workers provide answers to get rewards. Worker anonymity motivates participation since it protects their privacy. Anonymity with unlinkability is an enhanced version of anonymity because it makes it impossible to “link” workers across the tasks they participate in. Another core feature of crowdsourcing systems is worker quality which expresses a worker's trustworthiness and quantifies their historical performance. In this work, we present AVeCQ, the first crowdsourcing system that reconciles these properties, achieving enhanced anonymity and verifiable worker quality updates. AVeCQ relies on a suite of cryptographic tools, such as zero-knowledge proofs, to (i) guarantee workers’ privacy, (ii) prove the correctness of worker quality scores and task answers, and (iii) commensurate payments. AVeCQ is developed modularly, where requesters and workers communicate over a platform that supports pseudonymity, information logging, and payments. To compare AVeCQ with the state-ofthe-art, we prototype it over Ethereum. AVeCQ outperforms the state-of-the-art in three popular crowdsourcing tasks (image annotation, average review, and Gallup polls). E.g., for an Average Review task with 5 choices and 128 workers AVeCQ is 40% faster (including computing and verifying necessary proofs, and blockchain transaction processing overheads) with the task's requester consuming 87% fewer gas.

COVID-19 has altered the landscape of medical record issuing and verification. Multiple challenges have arisen in this new era as individuals are now required to prove their health status for traveling, working, or simply eating at a restaurant. Record verification across country borders is particularly hard to achieve as it requires collaboration at an international level, sharing potentially sensitive medical data. In this work, we propose VaxPass, a scalable system for COVID-19 record issuing and verification that facilitates this collaboration with minimal data leakage. At the core of our design lies a 2-tier blockchain architecture that allows individual issuing authorities to maintain their own 1st -level blockchain and only upload a small digest of their records, periodically, on the 2nd -level. Crucially, a verifier can check the validity of a certificate without having access to the 1st -level blockchain where the records actually reside. Our system also includes a mobile application and a web client. As we demonstrate, its performance scales well with the number of participants, making this the first solution able to support real-life inspired needs for such a system, while maintaining confidentiality of the medical data solely to privy entities.

We propose Agora, the first privacy-aware data marketplace that enables parties to get compensated for contributing data, without relying on a trusted third party. We leverage cryptographic techniques to achieve three security properties: (i) data privacy-raw data remain private except for a function output, (ii) output verifiability-the output is proven to be correct, and (iii) atomicity of payments-parties cannot avoid paying for provided services. Agora is designed as a decentralized blockchain application via smart contracts. We implement a prototype on Ethereum and evaluate its performance in terms of computation overhead and monetary cost.