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Smart Scan: An Approach to Detect Denial of Service Vulnerability in Ethereum Smart Contracts

Published: 17 April 2024 Publication History

Abstract

In this research, we introduce Smart Scan, an innovative approach designed to enhance the security of Ethereum smart contracts by detecting and mitigating Denial of Service (DoS) vulnerabilities. Smart Scan achieved an impressive accuracy rate of 89% in DoS vulnerability detection, surpassing the baseline accuracy of 84%. Additionally, the analysis of smart transactions initially achieved a baseline accuracy of 40%, shedding light on potential anomalies within Ethereum contracts, which combines static and dynamic analysis with a broad ensemble of machine learning algorithms. A 40% accuracy rate was also reached in the initial study of smart transactions, which helped to illuminate the possibility of anomalies in Ethereum contracts. By scanning for vulnerabilities before they can be exploited, Smart Scan helps developers and contract auditors make Ethereum's building blocks more bulletproof. To further solidify blockchain's position as the digital future's secure and transparent backbone, Smart Scan contributes to its continued development and adoption.

References

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Samreen, N.F. and M.H. Alalfi. Smartscan: an approach to detect denial of service vulnerability in ethereum smart contracts. in 2021 IEEE/ACM 4th International Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB). 2021. IEEE.
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Kushwaha, S.S., Ethereum smart contract analysis tools: A systematic review. IEEE Access, 2022. 10: p. 57037-57062.
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Ghaleb, A., J. Rubin, and K. Pattabiraman. eTainter: detecting gas-related vulnerabilities in smart contracts. in Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis. 2022.
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Nguyen, H.H., Mando: Multi-level heterogeneous graph embeddings for fine-grained detection of smart contract vulnerabilities. in 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA). 2022. IEEE.
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Rameder, H., M. Di Angelo, and G. Salzer, Review of automated vulnerability analysis of smart contracts on Ethereum. Frontiers in Blockchain, 2022. 5: p. 814977.
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Duan, L., Y. Sun, K. Zhang, and Y. Ding, Multiple-layer security threats on the ethereum blockchain and their countermeasures. Security and Communication Networks, 2022. 2022.
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Sürücü, O., A survey on ethereum smart contract vulnerability detection using machine learning. Disruptive Technologies in Information Sciences VI, 2022. 12117: p. 110-121.
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Kushwaha, S.S., Systematic review of security vulnerabilities in ethereum blockchain smart contract. IEEE Access, 2022. 10: p. 6605-6621.
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Yashavant, C.S., S. Kumar, and A. Karkare, Scrawld: A dataset of real world ethereum smart contracts labelled with vulnerabilities. arXiv preprint arXiv:2202.11409, 2022.
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Cited By

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  • (2024)An Intrusion Detection System For Detecting DDoS Attacks In Blockchain-Enabled IoMT Networks2024 7th International Conference on Signal Processing and Information Security (ICSPIS)10.1109/ICSPIS63676.2024.10812635(1-6)Online publication date: 12-Nov-2024

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  1. Smart Scan: An Approach to Detect Denial of Service Vulnerability in Ethereum Smart Contracts

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    EITCE '23: Proceedings of the 2023 7th International Conference on Electronic Information Technology and Computer Engineering
    October 2023
    1809 pages
    ISBN:9798400708305
    DOI:10.1145/3650400
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 17 April 2024

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    View all
    • (2024)An Intrusion Detection System For Detecting DDoS Attacks In Blockchain-Enabled IoMT Networks2024 7th International Conference on Signal Processing and Information Security (ICSPIS)10.1109/ICSPIS63676.2024.10812635(1-6)Online publication date: 12-Nov-2024

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