Learning to Pinpoint Emerging Software Vulnerabilities

学习查明新兴软件漏洞

• 批准号: DP210101348
• 负责人: A/Prof Yulei Sui
• 金额: $ 21.11万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP210101348
• 关键词: Learning; Pinpoint; Emerging; Software; Vulnerabilities

This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.

该项目旨在开发基于学习的软件漏洞检测技术，以提高现代软件系统的可靠性和安全性。现有的技术依赖于传统的但严格的软件分析和测试技术是无效的和/或低效的检测时，各种各样的新兴的软件漏洞。 该项目的成果将是一种基于深度学习的检测方法和一种开源工具，该工具可以捕获深度代码特征和各种漏洞之间的精确相关性，以查明新出现的漏洞，而无需bug规范。 显著的好处包括大大提高现代软件系统的质量、可靠性和安全性。