基于深度学习的方法用于智能合约中的漏洞检测
Zhibo Wang1, Liu Guoming2, Hongzhen Xu1
1College of Information Engineering, East China University of Technology, Nanchang, Jiangxi, China.
PeerJ. Computer science
|December 16, 2024
概括
本研究介绍了Ext-ttg,这是一个新的深度学习模型,用于检测智能合约中的多个漏洞. 它有效地识别了复杂的安全漏洞,改善了数字资产管理.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 人工智能的人工智能
背景情况:
- 智能合约对于数字资产管理至关重要,但容易受到安全漏洞的攻击.
- 现有的漏洞检测方法往往无法识别多个并存的漏洞.
研究的目的:
- 开发一种用于智能合约中综合多标签漏洞检测的新型模型.
- 为了解决当前单一漏洞检测技术的局限性.
主要方法:
- 提出了一个名为Ext-ttg的新型号.
- 集成的提取总结用于数据预处理.
- 采用定制深度学习架构用于漏洞检测.
主要成果:
- Ext-ttg模型在各种指标上表现出了值得称赞的表现.
- 成功检测到智能合约中的多个漏洞.
- 验证了综合方法的有效性.
结论:
- Ext-ttg模型为智能合约中多重漏洞检测提供了一个有效的解决方案.
- 这种方法通过改进智能合约分析来提高数字资产管理的安全性.
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