Fighting Under-price DoS Attack in Ethereum with Machine Learning Techniques
- 17 May 2021
- journal article
- research article
- Published by Association for Computing Machinery (ACM) in ACM SIGMETRICS Performance Evaluation Review
- Vol. 48 (4), 24-27
- https://doi.org/10.1145/3466826.3466835
Abstract
Ethereum is one of the most popular cryptocurrency currently and it has been facing security threats and attacks. As a consequence, Ethereum users may experience long periods to validate transactions. Despite the maintenance on the Ethereum mechanisms, there are still indications that it remains susceptible to a sort of attacks. In this work, we analyze the Ethereum network behavior during an under-priced DoS attack, where malicious users try to perform denial-of-service attacks that exploit flaws in the fee mechanism of this cryptocurrency. We propose the application of machine learning techniques and ensemble methods to detect this attack, using the available transaction attributes. The proposals present notable performance as the Decision Tree models, with AUC-ROC, F-score and recall larger than 0.94, 0.82, and 0.98, respectively.Keywords
This publication has 4 references indexed in Scilit:
- A Survey on Ethereum Systems SecurityACM Computing Surveys, 2020
- Mempool optimization for Defending Against DDoS Attacks in PoW-based Blockchain SystemsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2019
- An Adaptive Gas Cost Mechanism for Ethereum to Defend Against Under-Priced DoS AttacksPublished by Springer Science and Business Media LLC ,2017
- Stressing Out: Bitcoin “Stress Testing”Published by Springer Science and Business Media LLC ,2016