Image-Based Scam Detection Method Using an Attention Capsule Network

Lingyu Bian,Linlin Zhang,Hao Wang,Shengjia Gong,Kai Zhao

doi:10.1109/access.2021.3059806

Lingyu Bian, Linlin Zhang + Show 3 more

Open Access

https://doi.org/10.1109/access.2021.3059806

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Abstract

In recent years, the rapid development of blockchain technology has attracted much attention from people around the world. Scammers take advantage of the pseudo-anonymity of blockchain to implement financial fraud. The Ponzi scheme, one of the main scam methods, has defrauded investors of large amounts of money, thereby harming their interests and hindering the application of blockchain. Unfortunately, the current detection technology typically largely relies on the source code of the contract or uses a single feature which does not fully represent the contract characteristics. In such a case, the detection of Ponzi schemes with high efficiency becomes urgent. In this paper, we propose an image-based scam detection method using an attention capsule network (SE-CapsNet) focused on Ethereum. The sequence of bytecode, the opcode frequency, and the application binary interface (ABI) call are extracted as features from the contract bytecode and ABI, further converted into grayscale images, and then mapped into three color channels to generate RGB images, which are used as the input of the model for detecting the Ponzi scheme contract. In addition, we employ fancy PCA for data augmentation to reduce the impact of imbalanced data on the detection results. Experimental results show that the image-based detection method using deep learning models can effectively detect contracts before transactions occur. Among them, our proposed SE-CapsNet obtains great detection results, with an F1 score of 98.38%.

Highlights

After decades of development, blockchain has emerged as a technology with a wide range of applications, and it has attracted extensive attention from both academia and industry, especially in the field of cryptocurrency, where market valuations such as Bitcoin and Ether are rising at increasing rates
According to the latest research report published by Chainalysis [2], a blockchain analysis company, the total value of defrauded cryptocurrency was as high as 4.3 billion US dollars in 2019, and most of it came from Ponzi schemes
To some extent, we can say that the Ponzi scheme has damaged the reputation of the whole blockchain ecosystem, including Ethereum

Summary

Introduction

Blockchain has emerged as a technology with a wide range of applications, and it has attracted extensive attention from both academia and industry, especially in the field of cryptocurrency, where market valuations such as Bitcoin and Ether are rising at increasing rates. Under the lure of huge profits, due to the pseudo-anonymity of blockchain technology, scammers hidden behind pseudonymous accounts can complete cryptocurrency transactions as normal traders without their true intentions being identified [1]. According to the latest research report published by Chainalysis [2], a blockchain analysis company, the total value of defrauded cryptocurrency was as high as 4.3 billion US dollars in 2019, and most of it came from Ponzi schemes (up to 92%). To some extent, we can say that the Ponzi scheme has damaged the reputation of the whole blockchain ecosystem, including Ethereum

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