DEFENDING AGAINST POISONING ATTACKS IN FEDERATED LEARNING WITH BLOCKCHAIN

April 2025
Vol-11, Issue-2
Paper ID: 26143
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
INFORMATION TECHNOLOGY
Keywords
Federated learning (FL) decentralized systems blockchain malicious clients model aggregation serverless architecture secure machine learning collaborative learning robustness security and trustworthiness.
Abstract
In the era of deep learning, federated learning (FL) presents a promising approach that allows multiinstitutional data owners, or clients, to collaboratively train machine learning models without compromising data privacy. However, most existing FL approaches rely on a centralized server for global model aggregation, leading to a single point of failure. This makes the system vulnerable to malicious attacks when dealing with dishonest clients. In this work, we address this problem by proposing a secure and reliable FL system based on blockchain and distributed ledger technology. Our system incorporates a peer-to-peer voting mechanism and a reward-and-slash mechanism, which are powered by on-chain smart contracts, to detect and deter malicious behaviours. Both theoretical and empirical analyses are presented to demonstrate the effectiveness of the proposed approach, showing that our framework is robust against malicious client-side behaviours.

Author Information

# Name Institute / Affiliation
1 T.SUNDARARAJULU. SIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
2 RAJULA BADRINADH REDDY SIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
3 JAINI SAI PAVAN SIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
4 V.DIVYA SREE SIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
5 PEDDANABOYIENA TEJASWINI SIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
6 GUDIVETI VISWA TEJA SIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY

How to Cite

Use the following formats to cite this article in your research.

APA Style
T.SUNDARARAJULU., REDDY, RAJULA BADRINADH, PAVAN, JAINI SAI, SREE, V.DIVYA, TEJASWINI, PEDDANABOYIENA, & TEJA, GUDIVETI VISWA (2025). DEFENDING AGAINST POISONING ATTACKS IN FEDERATED LEARNING WITH BLOCKCHAIN. International Journal of Advance Research and Innovative Ideas In Education, 11(2), 1412-1419.
MLA Style
T.SUNDARARAJULU., et al. "DEFENDING AGAINST POISONING ATTACKS IN FEDERATED LEARNING WITH BLOCKCHAIN." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, 2025, pp. 1412-1419.
IEEE Style
T.SUNDARARAJULU., RAJULA BADRINADH REDDY, JAINI SAI PAVAN, V.DIVYA SREE, PEDDANABOYIENA TEJASWINI, and GUDIVETI VISWA TEJA, "DEFENDING AGAINST POISONING ATTACKS IN FEDERATED LEARNING WITH BLOCKCHAIN," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, pp. 1412-1419, 2025.
Vancouver Style
T.SUNDARARAJULU., REDDY RAJULA BADRINADH, PAVAN JAINI SAI, SREE V.DIVYA, TEJASWINI PEDDANABOYIENA, TEJA GUDIVETI VISWA. DEFENDING AGAINST POISONING ATTACKS IN FEDERATED LEARNING WITH BLOCKCHAIN. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(2):1412-1419.
Harvard Style
T.SUNDARARAJULU., REDDY, RAJULA BADRINADH, PAVAN, JAINI SAI, SREE, V.DIVYA, TEJASWINI, PEDDANABOYIENA, & TEJA, GUDIVETI VISWA (2025) 'DEFENDING AGAINST POISONING ATTACKS IN FEDERATED LEARNING WITH BLOCKCHAIN', International Journal of Advance Research and Innovative Ideas In Education, 11(2), pp. 1412-1419.
Chicago Style
T.SUNDARARAJULU., et al. "DEFENDING AGAINST POISONING ATTACKS IN FEDERATED LEARNING WITH BLOCKCHAIN." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 1412-1419.
Turabian Style
T.SUNDARARAJULU., et al. "DEFENDING AGAINST POISONING ATTACKS IN FEDERATED LEARNING WITH BLOCKCHAIN." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 1412-1419.

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