Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)

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Optimizing Phishing Detection in Ethereum Using Ensemble Learning

Authors
Piyush Kumar Ghosh1, *, Aditya Bhushan1, Dharmendra Kumar1, Ashutosh Kumar Singh2
1Department of Computer Science and Engineering, United College of Engineering and Research, Prayagraj, 211010, UP, India
2Department of Computer Science, Allahabad Degree College, University of Allahabad, Prayagraj, 211003, UP, India
*Corresponding author. Email: piyushkumarghosh1@gmail.com
Corresponding Author
Piyush Kumar Ghosh
Available Online 25 June 2025.
DOI
10.2991/978-94-6463-740-3_5How to use a DOI?
Keywords
Ethereum; Phishing Detection; Ensemble Learning; Blockchain Security; Decentralized System
Abstract

Among the various threats converging on the world of cryptocurrencies, the phishing attacks presented are among the most threatening ones within Ethereum. This paper introduces an innovative ensemble-based framework that enhances the detection of phishing attacks within Ethereum and mitigates against the basic shortcomings of traditional single-model approaches. Classifying with an accuracy of 98.5% and an F1-score of 97.0%, the stacked ensemble model demonstrates exceptional performance in predicting outcomes, highlighting its effectiveness in handling complex datasets and providing reliable results. These results therefore show the strength of this model in phishing threat identification and thus further improve performance. This approach leverages the strengths of multiple models to significantly enhance fraudulent activity detection on the Ethereum network. This work shows the importance of Ensemble Learning techniques in the general domain of blockchain security. The proposed model will thus act as a good benchmark for further study into this field of the future, with which one can obtain a strong solution to improve security for users.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)
Series
Advances in Intelligent Systems Research
Publication Date
25 June 2025
ISBN
978-94-6463-740-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-740-3_5How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Piyush Kumar Ghosh
AU  - Aditya Bhushan
AU  - Dharmendra Kumar
AU  - Ashutosh Kumar Singh
PY  - 2025
DA  - 2025/06/25
TI  - Optimizing Phishing Detection in Ethereum Using Ensemble Learning
BT  - Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)
PB  - Atlantis Press
SP  - 42
EP  - 52
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-740-3_5
DO  - 10.2991/978-94-6463-740-3_5
ID  - Ghosh2025
ER  -