On the scalable dynamic taint analysis for distributed systems

On the scalable dynamic taint analysis for distributed systems
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分布式系统的可扩展动态污点分析

DOI:
10.1145/3338906.3342506
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发表时间:
2019
期刊:
ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE
影响因子:
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通讯作者:
Fu, Xiaoqin
Fu, Xiaoqin
中科院分区:
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文献类型:
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作者:
Fu, Xiaoqin

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为了保护隐私和搜索敏感数据泄漏,我们必须解决多个挑战(例如,因此,我们提出DistTaint,一个动态的分布式系统的污点分析,针对这些挑战。它可以从执行中的偏序方法事件中推断出隐式依赖,以解决适用性挑战。DistTaint完全在应用程序级别工作,无需任何平台定制,以克服可移植性挑战。它利用多阶段分析来实现可扩展性。通过提出预分析,DistTaint缩小了以下细粒度分析的范围,从而显著降低了总体成本。实证结果表明,DistTaint的实用性,可移植性和可扩展性,工业规模的分布式程序,并在现实世界的分布式系统中发现安全漏洞的能力。该工具包可在此处下载:www.example.com dl = 0
To protect the privacy and search sensitive data leaks, we must solve multiple challenges (e.g., applicability, portability, and scalability) for developing an appropriate taint analysis for distributed systems.We hence present DistTaint, a dynamic taint analysis for distributed systems against these challenges. It could infer implicit dependencies from partial-ordering method events in executions to resolve the applicability challenge. DistTaint fully works at application-level without any customization of platforms to overcome the portability challenge. It exploits a multi-phase analysis to achieve scalability. By proposing a pre-analysis, DistTaint narrows down the following fine-grained analysis’ scope to reduce the overall cost significantly. Empirical results showed DistTaint’s practical applicability, portability, and scalability to industry-scale distributed programs, and its capability of discovering security vulnerabilities in real-world distributed systems. The tool package can be downloaded here: https://www.dropbox.com/sh/kfr9ixucyny1jp2/AAC00aI-I8O-d4ywZCqwZ1uaa?dl=0
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