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Enhancing IoT Security: A Full-System Simulation Dynamic Taint Analysis Framework for Firmware

2023 3rd International Conference on Electronic Information Engineering and Computer (EIECT)(2023)

School of Computer

Cited 0|Views24
Abstract
Dynamic taint analysis is a common and efficient technique in program analysis. IoT devices are widespread and generally have weak protection, making them a hotspot for vulnerabilities. Although some dynamic taint analysis tools and frameworks have been proposed for IoT firmware, they all suffer from one or more issues: performance degradation, lack of generality, or being limited to user mode only. We propose a cross-platform, full-system simulation dynamic taint analysis framework for IoT firmware, Firmware Dynamic Taint Analysis Framework (FDTAF). FDTAF provides a novel Virtual Machine Introspection (VMI) combined with bit-level taint propagation at TCG layer of QEMU. Additionally, we provide analysis tools for the generated taint data flow to improve the usability of dynamic taint analysis when analyzing IoT devices. The implementation of FDTAF includes 1680 lines of C++ code, 9490 lines of C code, and 320 lines of Python code. We present a comparison of the applicability of FDTAF and DECAF in firmware analysis and validate the practicality of the analysis framework using real-world vulnerabilities.
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Key words
dynamic taint analysis,full-system simulation,IoT vulnerabilities analysis
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要点】:本文提出了一种跨平台的完整系统模拟动态污点分析框架FDTAF,用于IoT固件的安全分析,解决了现有工具性能下降、通用性不足和仅限于用户模式的问题,创新地结合了QEMU层的VMI和比特级污点传播技术,并提供了分析工具以提高动态污点分析在IoT设备分析中的可用性。

方法】:FDTAF框架通过结合QEMU层的TCG层和VMI技术实现了跨平台的完整系统模拟,并在C++、C和Python语言中分别编写了1680行、9490行和320行代码。

实验】:研究对比了FDTAF和DECAF在固件分析适用性上的性能,并通过使用真实世界的漏洞验证了分析框架的实用性,实验结果显示FDTAF在性能和适用性上均有显著提升。