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Blockchain-based Distributed Ledgers (DLs) promise to transform the existing financial system by making it truly democratic. In the past decade, blockchain technology has seen many novel applications ranging from the banking industry to…
Despite the great potential of Federated Learning (FL) in large-scale distributed learning, the current system is still subject to several privacy issues due to the fact that local models trained by clients are exposed to the central…
Federated learning (FL) is a promising way to allow multiple data owners (clients) to collaboratively train machine learning models without compromising data privacy. Yet, existing FL solutions usually rely on a centralized aggregator for…
While the last few decades have witnessed a huge body of work devoted to inference and learning in distributed and decentralized setups, much of this work assumes a non-adversarial setting in which individual nodes---apart from occasional…
Hyperledger Fabric is an enterprise grade permissioned distributed ledger platform that offers modularity for a broad set of industry use cases. One modular component is a pluggable ordering service that establishes consensus on the order…
Sharding has emerged as a critical solution to address the scalability challenges faced by blockchain networks, enabling them to achieve higher transaction throughput, reduced latency, and optimized resource usage. This paper investigates…
The widespread adoption of blockchain technology has amplified the spectrum of potential threats to its integrity and security. The ongoing quest to exploit vulnerabilities emphasizes how critical it is to expand on current research…
In recent years, cloud computing has been developing rapidly and is widely used in various fields such as commerce and scientific research. However, security issues, including access control, are a very important problem in popularizing…
Hyperledger Fabric is a distributed operating system for permissioned blockchains hosted by the Linux Foundation. It is the first truly extensible blockchain system for running distributed applications at enterprise grade scale. To achieve…
The advent of decentralized trading markets introduces a number of new challenges for consensus protocols. In addition to the `usual' attacks -- a subset of the validators trying to prevent disagreement -- there is now the possibility of…
Blockchains offer trust and immutability in non-trusted environments, but most are not fast enough for latency-sensitive applications. Hyperledger Fabric (HF) is a common enterprise-level platform that is being offered as…
Federated learning is an emerging privacy-preserving AI technique where clients (i.e., organisations or devices) train models locally and formulate a global model based on the local model updates without transferring local data externally.…
We identify a subtle security issue that impacts the design of smart contracts, because agents may themselves deploy smart contracts (side contracts). Typically, equilibria of games are analyzed in vitro, under the assumption that players…
Mining fairness in blockchain refers to equality between the computational resources invested in mining and the block rewards received. There exists a dilemma wherein increasing the transaction processing capacity of a blockchain…
Smart contracts have enabled blockchain systems to evolve from simple cryptocurrency platforms, such as Bitcoin, to general transactional systems, such as Ethereum. Catering for emerging business requirements, a new architecture called…
Banks routinely use neural networks to make decisions. While these models offer higher accuracy, they are susceptible to adversarial attacks, a risk often overlooked in the context of event sequences, particularly sequences of financial…
Federated Learning (FL) is a distributed, and decentralized machine learning protocol. By executing FL, a set of agents can jointly train a model without sharing their datasets with each other, or a third-party. This makes FL particularly…
Since the inception of Bitcoin, the distributed systems community has shown interest in the design of efficient blockchain systems. However, initial blockchain applications (like Bitcoin) attain very low throughput, which has promoted the…
Blockchain technology and related frameworks have recently received extensive attention. Blockchain systems use multi-party consensus protocols to reach agreements on transactions. Hyperledger Fabric framework exposes a multi-party…
Ensuring that an AI system behaves reliably and as intended, especially in the presence of unexpected faults or adversarial conditions, is a complex challenge. Inspired by the field of Byzantine Fault Tolerance (BFT) from distributed…