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Article
Publication date: 14 July 2022

Pradyumna Kumar Tripathy, Anurag Shrivastava, Varsha Agarwal, Devangkumar Umakant Shah, Chandra Sekhar Reddy L. and S.V. Akilandeeswari

This paper aims to provide the security and privacy for Byzantine clients from different types of attacks.

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Abstract

Purpose

This paper aims to provide the security and privacy for Byzantine clients from different types of attacks.

Design/methodology/approach

In this paper, the authors use Federated Learning Algorithm Based On Matrix Mapping For Data Privacy over Edge Computing.

Findings

By using Softmax layer probability distribution for model byzantine tolerance can be increased from 40% to 45% in the blocking-convergence attack, and the edge backdoor attack can be stopped.

Originality/value

By using Softmax layer probability distribution for model the results of the tests, the aggregation method can protect at least 30% of Byzantine clients.

Details

International Journal of Pervasive Computing and Communications, vol. 20 no. 5
Type: Research Article
ISSN: 1742-7371

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