Zero-knowledge range proofs play a critical role in confidential transactions (CT) on blockchain systems. They are used to prove the non-negativity of committed transaction payments without disclosing the exact values. Logarithmicsized range proofs with transparent setups, e.g., Bulletproofs, which aim to prove a committed value lies in the range [0, 2 -1] where is the bit length of the range, have gained growing popularity for communication-critical blockchain systems as they increase scalability by allowing a block to accommodate more transactions. In this paper, we propose SwiftRange, a new type of logarithmic-sized zero-knowledge range argument with a transparent setup in the discrete logarithm setting. Our argument can be a drop-in replacement for range proofs in blockchain-based confidential transactions. Compared with Bulletproofs, our argument has higher computational efficiency and lower round complexity while incurring comparable communication overheads for CT-friendly ranges, where N ∈ {32, 64}. Specifically, a single SwiftRange achieves 1.73× and 1.37× proving efficiency with no more than 1.1× communication costs for both ranges, respectively. More importantly, our argument is doubly efficient in verification efficiency. Furthermore, our argument has a smaller size when N ≤ 16, making it competitive for many other communication-critical applications. Our argument supports the aggregation of multiple single arguments for greater efficiency in communication and verification. Finally, we benchmarked our argument against the state-of-the-art range proofs to demonstrate its practicality.

Bit-decomposition-based zero-knowledge range proofs in the discrete logarithm (DLOG) setting with a transparent setup, e.g., Bulletproof (IEEE S&P 18), Flashproof (ASIACRYPT 22), and SwiftRange (IEEE S&P 24), have garnered widespread popularity across various privacy-enhancing applications. These proofs aim to prove that a committed value falls within the non-negative range [0, 2^N-1] without revealing it, where N represents the bit length of the range. Despite their prevalence, the current implementations still suffer from suboptimal performance. Some exhibit reduced communication costs at the expense of increased computational costs while others experience the opposite. Presently, users are compelled to utilize these proofs in scenarios demanding stringent requirements for both communication and computation efficiency. In this paper, we introduce, FlashSwift, a stronger DLOG-based logarithmic-sized alternative. It stands out for its greater shortness and significantly enhanced computational efficiency compared with the cutting-edge logarithmic-sized ones for the most common ranges where N is no more than 64. It is developed by integrating the techniques from Flashproof and SwiftRange without using a trusted setup. The substantial efficiency gains stem from our dedicated efforts in overcoming the inherent incompatibility barrier between the two techniques. Specifically, when N=64, our proof achieves the same size as Bulletproof and exhibits 1.1 times communication efficiency of SwiftRange. More importantly, compared with the two, it achieves 2.3 times and 1.65 times proving efficiency, and 3.2 times and 1.7 times verification efficiency, respectively. At the time of writing, our proof also creates two new records of the smallest proof sizes, 289 bytes and 417 bytes, for 8-bit and 16-bit ranges among all the bit-decomposition-based ones without requiring trusted setups. Moreover, to the best of our knowledge, it is the first configurable range proof that is adaptable to various scenarios with different specifications, where the configurability allows to trade off communication efficiency for computational efficiency. In addition, we offer a bonus feature: FlashSwift supports the aggregation of multiple single proofs for efficiency improvement. Finally, we provide comprehensive performance benchmarks against the state-of-the-art ones to demonstrate its practicality.

Decentralizing crowdsourcing using blockchain removes the trusted mediator who may cause social biases in data aggregation and uncertainties in ensuring proper rewards to workers. Permissionless blockchain discloses all data on public ledgers, which compromises the privacy and anonymity of workers and induces free-riders. State-of-the-art anonymous crowdsourcing systems enable anonymity through identity registration of workers and a trusted setup for key generation. However, these systems fail to support anonymous payments to workers, which may compromise the identities of workers. In this paper, we incorporate anonymous payments in crowdsourcing and dispense with identity registration and trusted setup to support open anonymous participation from any worker. Our solution is based on the decentralized anonymous payment systems (e.g., Zerocoin), commitment schemes, and efficient non-interactive zero-knowledge proofs.

Cloud computing has been a dominant paradigm for a variety of information processing platforms, particularly for enabling various popular applications of sharing economy. However, there is a major concern regarding data privacy on these cloud-based platforms. This work presents novel cloud-based privacy-preserving solutions to support collaborative consumption applications for sharing economy. In typical collaborative consumption, information processing platforms need to enable fair cost-sharing among multiple users for utilizing certain shared facilities and communal services. Our cloud-based privacy-preserving protocols, based on homomorphic Paillier cryptosystems, can ensure that the cloud-based operator can only obtain an aggregate schedule of all users in facility sharing, or a service schedule conforming to service provision rule in communal service sharing, but is unable to track the personal schedules or demands of individual users. More importantly, the participating users are still able to settle cost-sharing among themselves in a fair manner for the incurred costs, without knowing each other’s private schedules or demands. Our privacy-preserving protocols involve no other third party who may compromise privacy. We also provide an extensive evaluation study and a proof-of-concept system prototype of our protocols.