Blockchain and distributed ledger technologies (DLTs) facilitate decentralized computations across trust boundaries. However, ensuring complex computations with low gas fees and confidentiality remains challenging. Recent advances in Confidential Computing —leveraging hardware-based Trusted Execution Environments (TEEs)—and Proof-carrying Data—employing cryptographic Zero-Knowledge Virtual Machines (zkVMs)—hold promise for secure, privacy-preserving off-chain and layer-2 computations. On the other side, a homogeneous reliance on a single technology, such as TEEs or zkVMs, is impractical for decentralized environments with heterogeneous computational requirements.This paper introduces the Trusted Compute Unit (TCU), a unifying framework that enables composable and interoperable verifiable computations across heterogeneous technologies. Our approach allows decentralized applications (dApps) to flexibly offload complex computations to TCUs, obtaining proof of correctness. These proofs can be anchored on-chain for automated dApps interactions, while ensuring confidentiality of input data, and integrity of output data.We demonstrate how TCUs can support a prominent blockchain use case, such as federated learning. By enabling secure, off-chain interactions without incurring on-chain confirmation delays or gas fees, TCUs significantly improve system performance and scalability. Experimental insights and performance evaluations confirm the feasibility and practicality of this unified approach, advancing the state of the art in verifiable off-chain services for the blockchain ecosystem.

Zk-SNARKs help scale blockchains with Verifiable Off-chain Computations (VOC). zk-SNARK DSL toolkits are key when designing arithmetic circuits but fall short of automating the subsequent proof-generation step in an automated manner. We emphasize the need for portability, interoperability, and manageability in VOC-based solutions and introduce a Proving Service that is designed to provide a scalable and reusable solution for generating zk-SNARK proofs leveraging clouds.

Verifiable decentralized federated learning (FL) systems combining blockchains and zero-knowledge proofs (ZKP) make the computational integrity of local learning and global aggregation verifiable across workers. However, they are not end-to-end: data can still be corrupted prior to the learning. In this paper, we propose a verifiable decentralized FL system for end-to-end integrity and authenticity of data and computation extending verifiability to the data source. Addressing an inherent conflict of confidentiality and transparency, we introduce a two-step proving and verification (2PV) method that we apply to central system procedures: a registration workflow that enables non-disclosing verification of device certificates and a learning workflow that extends existing blockchain and ZKP-based FL systems through non-disclosing data authenticity proofs. Our evaluation on a prototypical implementation demonstrates the technical feasibility with only marginal overheads to state-of-the-art solutions.

In face of the ongoing climate change, both reduction and offsetting of carbon emissions are critical. To this end, accurate, reliable emission data, and service-oriented architectures for processing the data are needed. Current carbon accounting practices, however, are often error-prone, costly, and time-consuming. Even in digital monitoring, reporting, and verification (MRV) systems, the employment of single, trusted verification bodies inhibits transparent, fine-granular, and verifiable accounting at product instance-level in high-throughput supply chains. We proposeVerifiable Carbon Accounting(VCA) as a novel accounting approach that leverages authenticity and zero-knowledge proofs in service-oriented architectures for creating non-disclosing emission reports that are peer-to-peer verifiable on blockchains. VCA builds upon and extends both conventional and digital MRV systems but ensures the confidentiality of business emission data and calculations while allowing for peer-to-peer transparency and verifiability. We introduce the concept and demonstrate VCA application for accounting product carbon footprints (PCFs) in supply chains. We present a proof-of-concept technical system design and implementation and discuss experimental findings, deriving both insights on VCA practicability and next steps. Overall, we show how VCA advances the state of the art in carbon accounting in and beyond supply chains, and how VCA can serve as the basis for next-generation, accurate carbon accounting.