论文标题
有关软件脆弱性协调的案例研究
A Case Study on Software Vulnerability Coordination
论文作者
论文摘要
上下文:协调是软件工程的基本宗旨。还需要协调,以识别具有常见漏洞和暴露(CVE)的发现和披露的软件漏洞。在最近的实际挑战中,本文通过公共邮件列表审查了CVE为开源项目的协调。目的:本文观察到CVE在邮件列表中的分配与在国家脆弱性数据库(NVD)中的后期出现之间的历史时间延迟。从软件工程协调,软件漏洞和错误跟踪的研究中,这些延迟是通过三个维度建模的:社交网络和通信实践,跟踪基础架构以及CVES协调的技术特征。方法:鉴于2008年至2016年之间的时期,使用了五千CVE的样本来对延迟进行建模近五十个解释指标。回归分析用于建模。结果:结果表明,CVE协调延迟受噪声和先决条件约束的不同抽象的影响。这些抽象传达了社交网络和基础设施维度的影响。对于年度和每月的控制指标,周末的控制度量,CVE协调网络中的节点的程度以及NVD中CVES存档的NVD中给出的参考文献数量,观察到了特别强大的效果大小。对于测量交换电子邮件的熵,错误跟踪系统的痕迹以及其他相关方面的指标,存在较小但可见的效果。对于技术特征,经验信号较弱。结论: [...]
Context: Coordination is a fundamental tenet of software engineering. Coordination is required also for identifying discovered and disclosed software vulnerabilities with Common Vulnerabilities and Exposures (CVEs). Motivated by recent practical challenges, this paper examines the coordination of CVEs for open source projects through a public mailing list. Objective: The paper observes the historical time delays between the assignment of CVEs on a mailing list and the later appearance of these in the National Vulnerability Database (NVD). Drawing from research on software engineering coordination, software vulnerabilities, and bug tracking, the delays are modeled through three dimensions: social networks and communication practices, tracking infrastructures, and the technical characteristics of the CVEs coordinated. Method: Given a period between 2008 and 2016, a sample of over five thousand CVEs is used to model the delays with nearly fifty explanatory metrics. Regression analysis is used for the modeling. Results: The results show that the CVE coordination delays are affected by different abstractions for noise and prerequisite constraints. These abstractions convey effects from the social network and infrastructure dimensions. Particularly strong effect sizes are observed for annual and monthly control metrics, a control metric for weekends, the degrees of the nodes in the CVE coordination networks, and the number of references given in NVD for the CVEs archived. Smaller but visible effects are present for metrics measuring the entropy of the emails exchanged, traces to bug tracking systems, and other related aspects. The empirical signals are weaker for the technical characteristics. Conclusion: [...]