相关论文: Handel: Practical Multi-Signature Aggregation for …

Both Byzantine resilience and communication efficiency have attracted tremendous attention recently for their significance in edge federated learning. However, most existing algorithms may fail when dealing with real-world irregular data…

This paper describes BigBFT, a multi-leader Byzantine fault tolerance protocol that achieves high throughput and scalable consensus in blockchain systems. BigBFT achieves this by (1) enabling every node to be a leader that can propose and…

Consensus is one of the most fundamental distributed computing problems. In particular, it serves as a building block in many replication based fault-tolerant systems and in particular in multiple recent blockchain solutions. Depending on…

Large scale cryptocurrencies require the participation of millions of participants and support economic activity of billions of dollars, which has led to new lines of work in binary Byzantine Agreement (BBA) and consensus. The new work aims…

This paper focuses on decentralized stochastic optimization in the presence of Byzantine attacks. During the optimization process, an unknown number of malfunctioning or malicious workers, termed as Byzantine workers, disobey the…

The spectacular success of Bitcoin and Blockchain Technology in recent years has provided enough evidence that a widespread adoption of a common cryptocurrency system is not merely a distant vision, but a scenario that might come true in…

This paper explores how reliable broadcast can be implemented without signatures when facing a dual adversary that can both corrupt processes and remove messages. More precisely, we consider an asynchronous $n$-process message-passing…

Byzantine-robust federated learning aims at mitigating Byzantine failures during the federated training process, where malicious participants may upload arbitrary local updates to the central server to degrade the performance of the global…

In machine learning security, one is often faced with the problem of removing outliers from a given set of high-dimensional vectors when computing their average. For example, many variants of data poisoning attacks produce gradient vectors…

This work describes two randomized, asynchronous, round based, Binary Byzantine faulty tolerant consensus algorithms based on the algorithms of [25] and [26]. Like the algorithms of [25] and [26] they do not use signatures, use $O(n^2)$…

In this paper, we study a linear bandit optimization problem in a federated setting where a large collection of distributed agents collaboratively learn a common linear bandit model. Standard federated learning algorithms applied to this…

Federated Learning (FL) enables decentralized model training without sharing raw data. However, it remains vulnerable to Byzantine attacks, which can compromise the aggregation of locally updated parameters at the central server.…

In this paper, we investigate the performance of the Tangle 2.0 consensus protocol in a Byzantine environment. We use an agent-based simulation model that incorporates the main features of the Tangle 2.0 consensus protocol. Our experimental…

Federated learning (FL) enables multiple clients to collaboratively train a global model without sharing their local data. Recent studies have highlighted the vulnerability of FL to Byzantine attacks, where malicious clients send poisoned…

In this paper we extend the \emph{Multidimensional Byzantine Agreement (MBA) Protocol}, a {leaderless} Byzantine agreement for lists of arbitrary values, into a protocol suitable for wide gossiping networks: \emph{Cob}. This generalization…

In this paper, we investigate the problem of distributed learning (DL) in the presence of Byzantine attacks. For this problem, various robust bounded aggregation (RBA) rules have been proposed at the central server to mitigate the impact of…

Byzantine agreement protocols in asynchronous networks have gained renewed attention due to their independence from network timing assumptions to ensure termination. Traditional asynchronous Byzantine agreement protocols require every party…

In this paper, we propose a robust aggregation method for federated learning (FL) that can effectively tackle malicious Byzantine attacks. At each user, model parameter is firstly updated by multiple steps, which is adjustable over…

Network coding increases throughput and is robust against failures and erasures. However, since it allows mixing of information within the network, a single corrupted packet generated by a Byzantine attacker can easily contaminate the…

This thesis proposes techniques aiming to make blockchain technologies and smart contract platforms practical by improving their scalability, latency, and privacy. This thesis starts by presenting the design and implementation of…