Distributed ledgers are enabling novel applications in traditional domains, such as finance, healthcare and supply chains, and in emerging domains such as metaverse. We observe that the current ecosystem is fragmented, with different blockchains operating in silos. Interledger applications that can access resources in different ledgers can tap into the billions of dollars worth of locked resources, but they require support for interledger communication. Existing interledger communications, however, are either insecure, inefficient, or application specific. Our goal is to design a system for interledger applications. To this end, we design and implement that achieves strong security guarantees and high performance while providing the general message passing abstraction to the applications. Our system leverages trusted hardware for performance and threshold signature schemes for strong security. It consists of multiple lightweight clients that verify transactions within their trusted execution environments before generating threshold signatures. We conduct extensive performance evaluations of and compare it against three state-of-the-art systems, namely WeCross, Cosmos IBC and LayerZero-V2. The results show that is efficient, achieving up to$42\times$higher throughput than the baselines.

In this paper, a variational Bayesian framework for simultaneous input and state estimation (VBSISE) is proposed. In VBSISE, probability density functions (PDFs) are assigned to inputs, with their parameters adaptively updated to enhance input estimation. This offers greater flexibility than existing methods that only handle fixed input conditions. Specifically, inputs are modeled using Gaussian and inverse Wishart distributions, and the joint PDF of the estimated variables is derived and approximated via the variational Bayesian approach to obtain tractable distributions. The input and state estimates are then obtained as the means of the approximated PDFs. The proposed VBSISE effectively adapts to input variations, unlike conventional methods that rely on fixed statistical moments. Experimental results demonstrate that the proposed VBSISE outperforms existing filters in both input and state estimation accuracy.

Federated learning (FL) is an emerging paradigm that enables multiple clients to collaboratively train a machine learning (ML) model without the need to exchange their raw data. However, it relies on a centralized authority to coordinate participants’ activities. This not only interrupts the entire training task in case of a single point of failure, but also lacks an effective regulatory mechanism to prevent malicious behavior. Although blockchain, with its decentralized architecture and data immutability, has significantly advanced the development of FL, it still struggles to withstand poisoning attacks and faces limitations in computational scalability. We propose Zkfhed, a verifiable and scalable FL system that overcomes the limitations of blockchain-based FL in poison attacks and computational scalability. First, we propose a two-stage audit scheme based on zero-knowledge proofs (ZKPs), which verifies that the training data are extracted from trusted organizations and that computations on the data exactly follow the specified training protocols. Second, we propose a homomorphic encryption delegation learning (HEDL), based on fully homomorphic encryption (FHE). It is capable of outsourcing complex computing to external computing resources without sacrificing the client's data privacy. Final, extensive experiments on real-world datasets demonstrate that Zkfhed can effectively identify malicious clients and is highly efficient and scalable in terms of online time and communication efficiency.

This paper presents a systematic and comprehensive survey on blockchain interoperability, where interoperability is defined as the ability of blockchains to flexibly transfer assets, share data, and invoke smart contracts across a mix of public, private, and consortium blockchains without any changes to the underlying blockchain systems. Analyzing the vast landscape of both research papers and industry projects, we classify the existing works into five categories, namely, (1) sidechains, (2) notary schemes, (3) hashed time lock contracts (HTLC), (4) relays, and (5) blockchain agnostic protocols. We analyze the existing works under a taxonomy that consists of system and safety characteristics, such as decentralization, direction of communication, locking mechanism, verification mechanism, trust, safety, liveness, and atomicity. Different from other surveys, we are the first to evaluate the performance of some representative interoperability approaches between Bitcoin and Ethereum covering sidechains, notary schemes, and HTLCs. Even though the performance of cross-chain transactions is low (typically fewer than 10 transactions per second), the main reason is the underlying blockchain (e.g., Bitcoin and Ethereum) and not the interoperability approach. Finally, we discuss existing challenges and possible research directions in blockchain interoperability. For example, we identify challenges in interoperability across permissioned and permissionless blockchains, in interacting with scripting blockchains, in security and privacy.