Abstract
For the purpose of discovering security flaws in software, many dynamic and static taint analyzing techniques have been proposed. The dynamic techniques can precisely find the security flaws of the software; but it suffers from substantial runtime overhead. On the other hand, the static techniques require no runtime overhead; but it is often not accurate enough. In this paper, we propose HYBit, a novel hybrid framework which integrates dynamic and static taint analysis to diagnose the security flaws for binary programs. In the framework, the source binary is first analyzed by the dynamic taint analyzer; then, with the runtime information provided by its dynamic counterpart, the static taint analyzer can process the unexecuted part of the target program easily. Furthermore, a taint behavior filtration mechanism is proposed to optimize the performance of the framework. We evaluate our framework from three perspectives: efficiency, coverage, and effectiveness, and the results are encouraging.
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Zhu, E., Guan, H., Liang, A., Xu, R., Li, X., Liu, F. (2013). HYBit: A Hybrid Taint Analyzing Framework for Binary Programs. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_28
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DOI: https://doi.org/10.1007/978-3-642-38715-9_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38714-2
Online ISBN: 978-3-642-38715-9
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