Differential Privacy (DP) is often presented as a strong privacy-enhancing technology with broad applicability and advocated as a de-facto standard for releasing aggregate statistics on sensitive data. However, in many embodiments, DP introduces a new attack surface: a malicious entity entrusted with releasing statistics could manipulate the results and use the randomness of DP as a convenient smokescreen to mask its nefariousness. Since revealing the random noise would obviate the purpose of introducing it, the miscreant may have a perfect alibi. To close this loophole, we introduce the idea of \textit{Verifiable Differential Privacy}, which requires the publishing entity to output a zero-knowledge proof that convinces an efficient verifier that the output is both DP and reliable. Such a definition might seem unachievable, as a verifier must validate that DP randomness was generated faithfully without learning anything about the randomness itself. We resolve this paradox by carefully mixing private and public randomness to compute verifiable DP counting queries with theoretical guarantees and show that it is also practical for real-world deployment. We also demonstrate that computational assumptions are necessary by showing a separation between information-theoretic DP and computational DP under our definition of verifiability.

In the wake of fraud scandals involving decentralized exchanges and the significant financial loss suffered by individuals, regulators are pressed to put mechanisms in place that enforce customer protections and capital requirements in decentralized ecosystems. Proof of liabilities (PoL) is such a mechanism: it allows a prover (e.g., an exchange) to prove its liability to a verifier (i.e., a customer).

A Hash Time Lock Contract (HTLC) is a protocol that is commonly used to exchange payments across different blockchains. Using HTLC as a building block for cross blockchain atomic swaps has its drawbacks: The notion of time is handled differently in each blockchain, be it private or public. Additionally, if the swap ends up aborted, the funds are locked in escrow until the safety timeout expires. In this work we formulate a new cryptographic primitive: Attribute Verifiable Timed Commitment which enables to prove that a timed commitment commits to a value which possesses certain attributes. Using our cryptographic primitive, we describe a new cross chain atomic swap protocol that operates without blockchain derived time and unlike the state of the art, all parties can instantly abort the swap without waiting for the safety timeouts to expire. In order to prove in zero knowledge that a secret committed to using a timed commitment has a claimed hash value, we employ the “MPC in the head” technique by Ishai et al. and implement our zero-knowledge proof protocol and evaluate its performance. As part of our techniques, we develop a novel and efficient procedure for integer Lower-Than validation in arithmetic circuits which may be of independent interest.

Introduction. The execute-order-validate blockchain architecture, introduced by Hyperledger Fabric (HLF) [1], allows parallel transactions execution and validation, thus raising the need for transaction isolation. Today transaction isolation is attained by locking the entire state database (DB) during simulation of transactions and state update. This lock is one of the major bottlenecks as observed by previous work [3]. This work presents a new lock-free approach for providing transaction isolation.

Fabric is a modular and extensible open-source system for deploying and operating permissioned blockchains and one of the Hyperledger projects hosted by the Linux Foundation (www.hyperledger.org).

No abstract available.

Distributed Ledger Technology (DLT) is rapidly emerging as a new paradigm for automating complex business processes in secure and decentralised fashion. Currently, however, its wider adoption is hampered by scalability problems [3] rooted in an inherent tension between stringent consistency, security, and robustness requirements on one hand, and growing application demand coupled with high performance expectations on the other. For example, popular peer-to-peer DLTs based on proof-of-work consensus [4] can only improve the transaction throughput by degrading their security and consistency guarantees, which is unacceptable in the enterprise and mission-critical settings.