FRAD: Front-Running Attacks Detection on Ethereum using Ternary Classification Model Article Swipe
Yuheng Zhang
,
Liu Pin
,
Guojun Wang
,
Peiqiang Li
,
Wanyi Gu
,
Houji Chen
,
Xuelei Liu
,
Jinyao Zhu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2311.14514
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2311.14514
With the evolution of blockchain technology, the issue of transaction security, particularly on platforms like Ethereum, has become increasingly critical. Front-running attacks, a unique form of security threat, pose significant challenges to the integrity of blockchain transactions. In these attack scenarios, malicious actors monitor other users' transaction activities, then strategically submit their own transactions with higher fees. This ensures their transactions are executed before the monitored transactions are included in the block. The primary objective of this paper is to delve into a comprehensive classification of transactions associated with front-running attacks, which aims to equip developers with specific strategies to counter each type of attack. To achieve this, we introduce a novel detection method named FRAD (Front-Running Attacks Detection on Ethereum using Ternary Classification Model). This method is specifically tailored for transactions within decentralized applications (DApps) on Ethereum, enabling accurate classification of front-running attacks involving transaction displacement, insertion, and suppression. Our experimental validation reveals that the Multilayer Perceptron (MLP) classifier offers the best performance in detecting front-running attacks, achieving an impressive accuracy rate of 84.59% and F1-score of 84.60%.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2311.14514
- https://arxiv.org/pdf/2311.14514
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389073236
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389073236Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2311.14514Digital Object Identifier
- Title
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FRAD: Front-Running Attacks Detection on Ethereum using Ternary Classification ModelWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-11-24Full publication date if available
- Authors
-
Yuheng Zhang, Liu Pin, Guojun Wang, Peiqiang Li, Wanyi Gu, Houji Chen, Xuelei Liu, Jinyao ZhuList of authors in order
- Landing page
-
https://arxiv.org/abs/2311.14514Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2311.14514Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2311.14514Direct OA link when available
- Concepts
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Blockchain, Computer science, Database transaction, Computer security, Classifier (UML), Front (military), Multilayer perceptron, Artificial intelligence, Database, Engineering, Artificial neural network, Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.insertion, | 147 |
| abstract_inverted_index.scenarios, | 40 |
| abstract_inverted_index.strategies | 98 |
| abstract_inverted_index.validation | 152 |
| abstract_inverted_index.activities, | 47 |
| abstract_inverted_index.performance | 163 |
| abstract_inverted_index.significant | 29 |
| abstract_inverted_index.technology, | 5 |
| abstract_inverted_index.transaction | 9, 46, 145 |
| abstract_inverted_index.applications | 134 |
| abstract_inverted_index.experimental | 151 |
| abstract_inverted_index.increasingly | 18 |
| abstract_inverted_index.particularly | 11 |
| abstract_inverted_index.specifically | 128 |
| abstract_inverted_index.suppression. | 149 |
| abstract_inverted_index.transactions | 53, 60, 66, 86, 131 |
| abstract_inverted_index.Front-running | 20 |
| abstract_inverted_index.comprehensive | 83 |
| abstract_inverted_index.decentralized | 133 |
| abstract_inverted_index.displacement, | 146 |
| abstract_inverted_index.front-running | 89, 142, 166 |
| abstract_inverted_index.strategically | 49 |
| abstract_inverted_index.transactions. | 36 |
| abstract_inverted_index.(Front-Running | 116 |
| abstract_inverted_index.Classification | 123 |
| abstract_inverted_index.classification | 84, 140 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile |