@inproceedings{71f7606ff7664ba0b535f475b77c8b37,
title = "Trade-offs in automatic provenance capture",
abstract = "Automatic provenance capture from arbitrary applications is a challenging problem. Different approaches to tackle this problem have evolved, most notably a. system-event trace analysis, b. compile-time static instrumentation, and c. taint flow analysis using dynamic binary instrumentation. Each of these approaches offers different trade-offs in terms of the granularity of captured provenance, integration requirements, and runtime overhead. While these aspects have been discussed separately, a systematic and detailed study, quantifying and elucidating them, is still lacking. To fill this gap, we begin to explore these trade-offs for representative examples of these approaches for automatic provenance capture by means of evaluation and measurement. We base our evaluation on UnixBench—a widely used benchmark suite within systems research. We believe this approach will make our results easier to compare with future studies.",
keywords = "LLVM, Provenance, SPADE, Strace, Taint tracking",
author = "Manolis Stamatogiannakis and Hasanat Kazmi and Hashim Sharif and Remco Vermeulen and Ashish Gehani and Herbert Bos and Paul Groth",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 6th International Provenance and Annotation Workshop, IPAW 2016 ; Conference date: 07-06-2016 Through 08-06-2016",
year = "2016",
doi = "10.1007/978-3-319-40593-3_3",
language = "Ingl{\'e}s",
isbn = "9783319405926",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "29--41",
editor = "Boris Glavic and Marta Mattoso",
booktitle = "Provenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings",
}