DifFuzzAR: automatic repair of timing side-channel vulnerabilities via refactoring

IF 2 2区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Automated Software Engineering Pub Date : 2023-10-18 DOI:10.1007/s10515-023-00398-6
Rui Lima, João F. Ferreira, Alexandra Mendes, Carolina Carreira
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Abstract

Vulnerability detection and repair is a demanding and expensive part of the software development process. As such, there has been an effort to develop new and better ways to automatically detect and repair vulnerabilities. DifFuzz is a state-of-the-art tool for automatic detection of timing side-channel vulnerabilities, a type of vulnerability that is particularly difficult to detect and correct. Despite recent progress made with tools such as DifFuzz, work on tools capable of automatically repairing timing side-channel vulnerabilities is scarce. In this paper, we propose DifFuzzAR, a tool for automatic repair of timing side-channel vulnerabilities in Java code. The tool works in conjunction with DifFuzz and it is able to repair 56% of the vulnerabilities identified in DifFuzz’s dataset. The results show that the tool can automatically correct timing side-channel vulnerabilities, being more effective with those that are control-flow based. In addition, the results of a user study show that users generally trust the refactorings produced by DifFuzzAR and that they see value in such a tool, in particular for more critical code.

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DifFuzzAR:通过重构自动修复定时侧信道漏洞
漏洞检测和修复是软件开发过程中一个要求很高且成本高昂的部分。因此,一直在努力开发新的更好的方法来自动检测和修复漏洞。DifFuzz是一种最先进的工具,用于自动检测定时侧信道漏洞,这种漏洞特别难以检测和纠正。尽管DifFuzz等工具最近取得了进展,但开发能够自动修复定时侧通道漏洞的工具的工作却很少。在本文中,我们提出了DifFuzzAR,一种用于自动修复Java代码中定时侧通道漏洞的工具。该工具与DifFuzz协同工作,能够修复DifFutz数据集中发现的56%的漏洞。结果表明,该工具可以自动纠正定时侧通道漏洞,与基于控制流的漏洞相比更有效。此外,一项用户研究的结果表明,用户通常信任DifFuzzAR产生的重构,他们看到了这种工具的价值,尤其是对于更关键的代码。
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来源期刊
Automated Software Engineering
Automated Software Engineering 工程技术-计算机:软件工程
CiteScore
4.80
自引率
11.80%
发文量
51
审稿时长
>12 weeks
期刊介绍: This journal details research, tutorial papers, survey and accounts of significant industrial experience in the foundations, techniques, tools and applications of automated software engineering technology. This includes the study of techniques for constructing, understanding, adapting, and modeling software artifacts and processes. Coverage in Automated Software Engineering examines both automatic systems and collaborative systems as well as computational models of human software engineering activities. In addition, it presents knowledge representations and artificial intelligence techniques applicable to automated software engineering, and formal techniques that support or provide theoretical foundations. The journal also includes reviews of books, software, conferences and workshops.
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