Hide and Seek: An Adversarial Hiding Approach Against Phishing Detection on Ethereum
【Author】 Wen, Haixian; Fang, Junyuan; Wu, Jiajing; Zheng, Zibin
【Source】IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
【影响因子】4.747
【Abstract】With the wide application and development of blockchain technology, the past years have witnessed the emergence of various cybercrimes, which have caused a huge amount of economic loss. Among them, phishing scams on the blockchain are regarded as a serious threat to the trading security of the blockchain ecosystem. By modeling the transaction data of blockchain as a network, a series of graph-based phishing detection frameworks have been proposed. Enlightened by adversarial attacks of graph data, we propose to verify the robustness of current phishing detection frameworks under intentional attackers aiming to hide phishing behaviors. In this study, we first propose a general phishing detection framework based on feature engineering and then propose a phishing hiding framework combing the greedy selection mechanism with four phishing hiding strategies to measure the robustness of the proposed general detection models. Extensive experiments evaluate the detective performance of the phishing detection model and its robustness against the hiding framework. The experimental results indicate that the detective model based on feature engineering is rather fragile under adversarial attacks.
【Keywords】Phishing; Blockchains; Feature extraction; Robustness; Perturbation methods; Computer crime; Biological system modeling; Adversarial attacks; blockchain; Ethereum; phishing detection; phishing hiding
【发表时间】
【收录时间】2022-09-28
【文献类型】实证数据
【主题类别】
区块链治理-技术治理-异常/非法交易识别
wangjiaxin
今天有1篇链上数据分析相关文章,https://doi.org/10.1109/TCSS.2022.3203081,发表在《IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS》,通过将区块链的交易数据建模为一个网络,提出了一系列基于图特征工程的钓鱼通用检测框架。受图数据对抗性攻击的启发,又提出了一个结合贪婪选择机制的钓鱼隐藏框架,以衡量所提出的通用检测模型的鲁棒性。实验结果表明,基于特征工程的通用检测模型在对抗攻击下十分脆弱。
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