Related papers: Network Coding for Delay Tolerant Networks with By…

WITHDRAWAL NOTICE This paper has been withdrawn by the authors as required by the American Journal of Sociology, which has accepted the paper for publication. AJS will not publish papers if the preprint remains posted on arXiv.

Adversarial attacks attempt to disrupt the training, retraining and utilizing of artificial intelligence and machine learning models in large-scale distributed machine learning systems. This causes security risks on its prediction outcome.…

Delay tolerant Ad-hoc Networks make use of mobility of relay nodes to compensate for lack of permanent connectivity and thus enable communication between nodes that are out of range of each other. To decrease delivery delay, the information…

This paper has been withdrawn by the author.

We describe an approach to modelling a Byzantine tolerant distributed algorithm as a family of related finite state machines, generated from a single meta-model. Various artefacts are generated from each state machine, including diagrams…

This paper has been withdrawn by the corresponding author because the newest version is now published in Journal of Discrete Algorithms.

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The recent advances in sensor technologies and smart devices enable the collaborative collection of a sheer volume of data from multiple information sources. As a promising tool to efficiently extract useful information from such big data,…

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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…

This paper has been withdrawn by the author, due to the insecurity against attacks received in quant-ph/0605027v5.

This paper considers the problem of Byzantine fault tolerance in distributed linear regression in a multi-agent system. However, the proposed algorithms are given for a more general class of distributed optimization problems, of which…

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Distributed model training needs to be adapted to challenges such as the straggler effect and Byzantine attacks. When coordinating the training process with multiple computing nodes, ensuring timely and reliable gradient aggregation amidst…

This paper has been withdrawn by the author due to a new work in [arXiv:0901.0456v4] which can contain the results in this paper.

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Numerous distributed tasks have to be handled in a setting where a fraction of nodes behaves Byzantine, that is, deviates arbitrarily from the intended protocol. Resilient, deterministic protocols rely on the detection of majorities to…

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This paper has been withdrawn by the author due to similarity to Author's other paper