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Related papers: The BG-simulation for Byzantine Mobile Robots

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This paper focuses on the problem of adversarial attacks from Byzantine machines in a Federated Learning setting where non-Byzantine machines can be partitioned into disjoint clusters. In this setting, non-Byzantine machines in the same…

Machine Learning · Statistics 2023-06-02 Zhixu Tao , Kun Yang , Sanjeev R. Kulkarni

In this work, we extend the topology-based approach for characterizing computability in asynchronous crash-failure distributed systems to asynchronous Byzantine systems. We give the first theorem with necessary and sufficient conditions to…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-06-11 Hammurabi Mendes , Christine Tasson , Maurice Herlihy

The gathering over meeting nodes problem requires the robots to gather at one of the pre-defined meeting nodes. This paper investigates the problem with respect to the objective function that minimizes the total number of moves made by all…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-16 Subhash Bhagat , Abhinav Chakraborty , Bibhuti Das , Krishnendu Mukhopadhyaya

A swarm of anonymous oblivious mobile robots, operating in deterministic Look-Compute-Move cycles, is confined within a circular track. All robots agree on the clockwise direction (chirality), they are activated by an adversarial…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-19 Giuseppe A. Di Luna , Ryuhei Uehara , Giovanni Viglietta , Yukiko Yamauchi

We consider the problem of distributed statistical machine learning in adversarial settings, where some unknown and time-varying subset of working machines may be compromised and behave arbitrarily to prevent an accurate model from being…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-10-24 Yudong Chen , Lili Su , Jiaming Xu

Distributed multi-task learning provides significant advantages in multi-agent networks with heterogeneous data sources where agents aim to learn distinct but correlated models simultaneously.However, distributed algorithms for learning…

Machine Learning · Computer Science 2021-01-11 Jiani Li , Waseem Abbas , Xenofon Koutsoukos

Anonymous mobile robots are often classified into synchronous, semi-synchronous and asynchronous robots when discussing the pattern formation problem. For semi-synchronous robots, all patterns formable with memory are also formable without…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-11-08 Taisuke Izumi , Samia Souissi , Yoshiaki Katayama , Nobuhiro Inuzuka , Xavier Défago , Koichi Wada , Masafumi Yamashita

We propose a novel relaxation of the classic asynchronous network model, called the random asynchronous model, which removes adversarial message scheduling while preserving unbounded message delays and Byzantine faults. Instead of an…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-27 George Danezis , Jovan Komatovic , Lefteris Kokoris-Kogias , Alberto Sonnino , Igor Zablotchi

The gathering over meeting nodes problem asks the robots to gather at one of the pre-defined meeting nodes. The robots are deployed on the nodes of an anonymous two-dimensional infinite grid which has a subset of nodes marked as meeting…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-22 Subhash Bhagat , Abhinav Chakraborty , Bibhuti Das , Krishnendu Mukhopadhyaya

Self-stabilization is a versatile approach to fault-tolerance since it permits a distributed system to recover from any transient fault that arbitrarily corrupts the contents of all memories in the system. Byzantine tolerance is an…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-05-31 Swan Dubois , Toshimitsu Masuzawa , Sébastien Tixeuil

In this paper, we study the challenging task of Byzantine-robust decentralized training on arbitrary communication graphs. Unlike federated learning where workers communicate through a server, workers in the decentralized environment can…

Machine Learning · Computer Science 2023-04-21 Lie He , Sai Praneeth Karimireddy , Martin Jaggi

We analyze the impact of transient and Byzantine faults on the construction of a maximal independent set in a general network. We adapt the self-stabilizing algorithm presented by Turau \cite{turau2007linear} for computing such a vertex…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-17 Johanne Cohen , Laurence Pilard , Jonas Sénizergues

We study a distributed computation problem in the presence of Byzantine workers where a central node wishes to solve a task that is divided into independent sub-tasks, each of which needs to be solved correctly. The distributed computation…

Information Theory · Computer Science 2025-07-23 Aayush Rajesh , Nikhil Karamchandani , Vinod M. Prabhakaran

Federated learning has exhibited vulnerabilities to Byzantine attacks, where the Byzantine attackers can send arbitrary gradients to a central server to destroy the convergence and performance of the global model. A wealth of robust…

Machine Learning · Computer Science 2023-06-06 Yuchen Liu , Chen Chen , Lingjuan Lyu , Fangzhao Wu , Sai Wu , Gang Chen

Self-stabilization is an versatile approach to fault-tolerance since it permits a distributed system to recover from any transient fault that arbitrarily corrupts the contents of all memories in the system. Byzantine tolerance is an…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-05-20 Swan Dubois , Toshimitsu Masuzawa , Sébastien Tixeuil

Federated Learning (FL) enables clients to collaboratively train a global model without sharing their private data. However, the presence of malicious (Byzantine) clients poses significant challenges to the robustness of FL, particularly…

Machine Learning · Computer Science 2026-05-26 Javad Parsa , Amir Hossein Daghestani , André M. H. Teixeira , Mikael Johansson

In Byzantine collaborative learning, $n$ clients in a peer-to-peer network collectively learn a model without sharing their data by exchanging and aggregating stochastic gradient estimates. Byzantine clients can prevent others from…

Machine Learning · Computer Science 2025-04-08 Mélanie Cambus , Darya Melnyk , Tijana Milentijević , Stefan Schmid

We present new protocols for Byzantine state machine replication and Byzantine agreement in the synchronous and authenticated setting. The celebrated PBFT state machine replication protocol tolerates $f$ Byzantine faults in an asynchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-14 Ittai Abraham , Srinivas Devadas , Danny Dolev , Kartik Nayak , Ling Ren

We define and investigate the consensus problem for a set of $N$ processes embedded on the $d$-dimensional plane, $d\geq 2$, which we call the {\em geoconsensus} problem. The processes have unique coordinates and can communicate with each…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-07 Joseph Oglio , Kendric Hood , Gokarna Sharma , Mikhail Nesterenko

We analyze the impact of transient and Byzantine faults on the construction of a maximal independent set in a general network. We adapt the self-stabilizing algorithm presented by Turau `for computing such a vertex set. Our algorithm is…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-11 Johanne Cohen , Laurence Pilard , François Pirot , Jonas Sénizergues