Field-Based Static Taint Analysis for Industrial Microservices

Zexin Zhong, Jiangchao Liu, Diyu Wu, Peng Di, Yulei Sui, A. Liu
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引用次数: 3

Abstract

Taint analysis is widely used for tracing sensitive data. However, the state-of-the-art taint analyzers face challenges on recall, scalability, and precision when applied on industrial microservices. To overcome these challenges, we present a field-based static taint analysis approach, which does not distinguish different instances of the same type but distinguishes fields of the same kind for tracing sensitive data on industrial microservices. The experimental results demonstrate that our approach is practical in industrial scenarios.
基于现场的工业微服务静态污点分析
污点分析被广泛用于跟踪敏感数据。然而,最先进的污染分析仪在应用于工业微服务时面临召回、可扩展性和精度方面的挑战。为了克服这些挑战,我们提出了一种基于字段的静态污染分析方法,该方法不区分相同类型的不同实例,而是区分用于跟踪工业微服务上敏感数据的相同类型的字段。实验结果表明,我们的方法在工业场景中是实用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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