Looking Inside the Black-Box: Capturing Data Provenance Using Dynamic Instrumentation
作者： Manolis Stamatogiannakis , Paul Groth , Herbert Bos
DOI: 10.1007/978-3-319-16462-5_12
关键词:
摘要: Knowing the provenance of a data item helps in ascertaining its trustworthiness. Various approaches have been proposed to track or infer provenance. However, these either treat an executing program as black-box, limiting fidelity captured provenance, require developers modify make it provenance-aware. In this paper, we introduce DataTracker, new approach capturing based on taint tracking, technique widely used security and reverse engineering fields. Our system is able identify relations through dynamic instrumentation unmodified binaries, without requiring access to, knowledge of, their source code. Hence, can for variety well-known applications. Because DataTracker looks inside program, captures high-fidelity accurate
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