scholarly journals Making Chord Robust to Byzantine Attacks

2005 ◽  
pp. 803-814 ◽  
Author(s):  
Amos Fiat ◽  
Jared Saia ◽  
Maxwell Young
Keyword(s):  
Byzantine Attacks

scholarly journals RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets

2019 ◽  
Vol 33 ◽  
pp. 1544-1551 ◽  
Author(s):  
Liping Li ◽  
Wei Xu ◽  
Tianyi Chen ◽  
Georgios B. Giannakis ◽  
Qing Ling
Keyword(s):  
Optimal Solution ◽  
Distributed Learning ◽  
Learning Task ◽  
Descent Method ◽  
Stochastic Gradient Descent ◽  
Subgradient Methods ◽  
Gradient Descent Method ◽  
Aggregation Methods ◽  
Heterogeneous Datasets ◽  
Byzantine Attacks

In this paper, we propose a class of robust stochastic subgradient methods for distributed learning from heterogeneous datasets at presence of an unknown number of Byzantine workers. The Byzantine workers, during the learning process, may send arbitrary incorrect messages to the master due to data corruptions, communication failures or malicious attacks, and consequently bias the learned model. The key to the proposed methods is a regularization term incorporated with the objective function so as to robustify the learning task and mitigate the negative effects of Byzantine attacks. The resultant subgradient-based algorithms are termed Byzantine-Robust Stochastic Aggregation methods, justifying our acronym RSA used henceforth. In contrast to most of the existing algorithms, RSA does not rely on the assumption that the data are independent and identically distributed (i.i.d.) on the workers, and hence fits for a wider class of applications. Theoretically, we show that: i) RSA converges to a near-optimal solution with the learning error dependent on the number of Byzantine workers; ii) the convergence rate of RSA under Byzantine attacks is the same as that of the stochastic gradient descent method, which is free of Byzantine attacks. Numerically, experiments on real dataset corroborate the competitive performance of RSA and a complexity reduction compared to the state-of-the-art alternatives.

scholarly journals DEPENDABILITY EVALUATION OF CLUSTER-BASED DISTRIBUTED SYSTEMS

2011 ◽  
Vol 22 (05) ◽  
pp. 1123-1142 ◽  
Author(s):  
EMMANUELLE ANCEAUME ◽  
FRANCISCO BRASILEIRO ◽  
ROMARIC LUDINARD ◽  
BRUNO SERICOLA ◽  
FRÉDÉRIC TRONEL
Keyword(s):  
Distributed Systems ◽  
Overlay Networks ◽  
Stationary Regime ◽  
Peer To Peer ◽  
Distributed Hash Tables ◽  
Hash Tables ◽  
Malicious Nodes ◽  
Initial Amount ◽  
Dependability Evaluation ◽  
Byzantine Attacks

Awerbuch and Scheideler have shown that peer-to-peer overlay networks can survive Byzantine attacks only if malicious nodes are not able to predict what will be the topology of the network for a given sequence of join and leave operations. In this paper we investigate adversarial strategies by following specific protocols. Our analysis demonstrates first that an adversary can very quickly subvert overlays based on distributed hash tables by simply never triggering leave operations. We then show that when all nodes (honest and malicious ones) are imposed on a limited lifetime, the system eventually reaches a stationary regime where the ratio of polluted clusters is bounded, independently from the initial amount of corruption in the system.

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