GAN-Enabled Code Embedding for Reentrant Vulnerabilities Detection

Hui Zhao, Peng Su, Yihang Wei, Keke Gai*, Meikang Qiu

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

As one of the key components of blockchain, smart contract is playing a vital role in achieving auto-functions; however, reentrant attacks are threatening the implementation of smart contracts, which limits the adoption of blockchain systems in various scenarios. To address this issue, we propose a reentrant vulnerability detection model based on word embedding, similarity detection, and Generative Adversarial Networks (GAN). Additionally, we provide a new approach for dynamically preventing reentrant attacks. We also implement experiments to evaluate our model and results show our scheme achieves 92% detecting accuracy for reentrant attack detection.

源语言英语
主期刊名Knowledge Science, Engineering and Management - 14th International Conference, KSEM 2021, Proceedings
编辑Han Qiu, Cheng Zhang, Zongming Fei, Meikang Qiu, Sun-Yuan Kung
出版商Springer Science and Business Media Deutschland GmbH
585-597
页数13
ISBN(印刷版)9783030821524
DOI
出版状态已出版 - 2021
活动14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021 - Tokyo, 日本
期限: 14 8月 202116 8月 2021

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12817 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021
国家/地区日本
Tokyo
时期14/08/2116/08/21

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