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Federated learning is a newly emerging distributed learning framework that facilitates the collaborative training of a shared global model among distributed participants with their privacy preserved. However, federated learning systems are…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-10-14 Minghui Li , Wei Wan , Jianrong Lu , Shengshan Hu , Junyu Shi , Leo Yu Zhang , Man Zhou , Yifeng Zheng

Federated Learning (FL) enables collaborative model training without sharing raw data. However, shared local model updates remain vulnerable to inference and poisoning attacks. Secure aggregation schemes have been proposed to mitigate these…

Machine Learning · Computer Science 2026-02-27 Arnab Nath , Harsh Kasyap

Adversarial attacks pose a major challenge to distributed learning systems, prompting the development of numerous robust learning methods. However, most existing approaches suffer from the curse of dimensionality, i.e. the error increases…

Machine Learning · Computer Science 2025-11-19 Wenyu Liu , Tianqiang Huang , Pengfei Zhang , Zong Ke , Minghui Min , Puning Zhao

Quantum simulation is a promising near term application for mesoscale quantum information processors, with the potential to solve computationally intractable problems at the scale of just a few dozen interacting quantum systems. Recent…

Quantum Physics · Physics 2014-08-14 David L. Hayes , Steven T. Flammia , Michael J. Biercuk

This paper demonstrates and proves that the coordination of actions in a distributed swarm can be enhanced by using quantum entanglement. In particular, we focus on - Global and local simultaneous random walks, using entangled qubits that…

Quantum Physics · Physics 2022-10-20 Yotam Ashkenazi , Shlomi Dolev

We present an event-driven simulation package called QuISP for large-scale quantum networks built on top of the OMNeT++ discrete event simulation framework. Although the behavior of quantum networking devices have been revealed by recent…

Byzantine reliable broadcast is a fundamental problem in distributed computing, which has been studied extensively over the past decades. State-of-the-art algorithms are predominantly based on the approach to share encoded fragments of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-06 Thomas Locher

Current quantum neural networks suffer from extreme sensitivity to both adversarial perturbations and hardware noise, creating a significant barrier to real-world deployment. Existing robustness techniques typically sacrifice clean accuracy…

Quantum Physics · Physics 2026-01-27 Mohamed Afane , Quanjiang Long , Haoting Shen , Ying Mao , Junaid Farooq , Ying Wang , Juntao Chen

SBFT is a state of the art Byzantine fault tolerant permissioned blockchain system that addresses the challenges of scalability, decentralization and world-scale geo-replication. SBFTis optimized for decentralization and can easily handle…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-03 Guy Golan Gueta , Ittai Abraham , Shelly Grossman , Dahlia Malkhi , Benny Pinkas , Michael K. Reiter , Dragos-Adrian Seredinschi , Orr Tamir , Alin Tomescu

Quorum is a permissioned blockchain platform built from the Ethereum codebase with adaptations to make it a permissioned consortium platform. It is one of the key contenders in the permissioned ledger space. Quorum supports confidentiality…

Cryptography and Security · Computer Science 2018-09-11 Arati Baliga , I Subhod , Pandurang Kamat , Siddhartha Chatterjee

In order to bring quantum networks into the real world, we would like to determine the requirements of quantum network protocols including the underlying quantum hardware. Because detailed architecture proposals are generally too complex…

Detection and mitigation of Byzantine behaviors in a decentralized learning setting is a daunting task, especially when the data distribution at the users is heterogeneous. As our main contribution, we propose Basil, a fast and…

Systems and Control · Electrical Eng. & Systems 2022-10-07 Ahmed Roushdy Elkordy , Saurav Prakash , A. Salman Avestimehr

In large-scale distributed learning, security issues have become increasingly important. Particularly in a decentralized environment, some computing units may behave abnormally, or even exhibit Byzantine failures -- arbitrary and…

Machine Learning · Computer Science 2021-02-26 Dong Yin , Yudong Chen , Kannan Ramchandran , Peter Bartlett

Consensus algorithms provide strategies to solve problems in a distributed system with the added constraint that data can only be shared between adjacent computing nodes. We find these algorithms in applications for wireless and sensor…

Cryptography and Security · Computer Science 2016-11-15 Michel Toulouse , Hai Le , Cao Vien Phung , Denis Hock

In collaborative and distributed learning, Byzantine robustness reflects a major facet of optimization algorithms. Such distributed algorithms are often accompanied by transmitting a large number of parameters, so communication compression…

Machine Learning · Computer Science 2026-04-07 Yanghao Li , Changxin Liu , Yuhao Yi

We develop a distributed second order optimization algorithm that is communication-efficient as well as robust against Byzantine failures of the worker machines. We propose COMRADE (COMunication-efficient and Robust Approximate Distributed…

Machine Learning · Computer Science 2021-03-19 Avishek Ghosh , Raj Kumar Maity , Arya Mazumdar

Modern distributed systems face growing security threats, as attackers continuously enhance their skills and vulnerabilities span across the entire system stack, from hardware to the application layer. In the system design phase, fault…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-07 Silvia Bonomi , Giovanni Farina , Roy Friedman , Eviatar B. Procaccia , Sebastien Tixeuil

With the rapid development of blockchain, Byzantine fault-tolerant protocols have attracted revived interest recently. To overcome the theoretical bounds of Byzantine fault tolerance, many protocols attempt to use Trusted Execution…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-07-07 Jiashuo Zhang , Jianbo Gao , Ke Wang , Zhenhao Wu , Ying Lan , Zhi Guan , Zhong Chen

We proposed a framework of quantum-enhanced logic-based blockchain, which improves the efficiency and power of quantum-secured blockchain. The efficiency is improved by using a new quantum honest-success Byzantine agreement protocol to…

Quantum Physics · Physics 2018-07-17 Xin Sun , Quanlong Wang , Piotr Kulicki , Xishun Zhao

Distributed machine learning algorithms enable learning of models from datasets that are distributed over a network without gathering the data at a centralized location. While efficient distributed algorithms have been developed under the…

Machine Learning · Computer Science 2020-07-07 Zhixiong Yang , Waheed U. Bajwa
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