nach oben

Erschienen in:

2015 | OriginalPaper | Buchkapitel

Looking Inside the Black-Box: Capturing Data Provenance Using Dynamic Instrumentation

verfasst von : Manolis Stamatogiannakis, Paul Groth, Herbert Bos

Erschienen in: Provenance and Annotation of Data and Processes

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Knowing the provenance of a data item helps in ascertaining its trustworthiness. Various approaches have been proposed to track or infer data provenance. However, these approaches either treat an executing program as a black-box, limiting the fidelity of the captured provenance, or require developers to modify the program to make it provenance-aware. In this paper, we introduce DataTracker, a new approach to capturing data provenance based on taint tracking, a technique widely used in the security and reverse engineering fields. Our system is able to identify data provenance relations through dynamic instrumentation of unmodified binaries, without requiring access to, or knowledge of, their source code. Hence, we can track provenance for a variety of well-known applications. Because DataTracker looks inside the executing program, it captures high-fidelity and accurate data provenance.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Applying Provenance to Protect Attribution in Distributed Computational Scientific Experiments

Nächstes Kapitel Generating Scientific Documentation for Computational Experiments Using Provenance

The source code of DataTracker is available on: http://github.com/m000/dtracker.

E.g. Perl taint mode: http://perldoc.perl.org/perlsec.html#Taint-mode.

Source code available on: https://git.cs.vu.nl/r.vermeulen/libdft.

For simplicity, we prefer the term “file” over the more accurate “file-like resource”.

http://www.w3.org/2011/prov/wiki/Diagrams.

A common placeholder text which has been used by typesetters since the 1500s.

Bosman, E., Slowinska, A., Bos, H.: Minemu: the world’s fastest taint tracker. In: Sommer, R., Balzarotti, D., Maier, G. (eds.) RAID 2011. LNCS, vol. 6961, pp. 1–20. Springer, Heidelberg (2011) CrossRef

Bowers, S., McPhillips, T.M., Ludaescher, B.: Provenance in collection-oriented scientific workflows. Concurr. Comput. Pract. Exper. 20(5), 519–529 (2008)CrossRef

Bruening, D.L.: Efficient, transparent, and comprehensive runtime code manipulation. Ph.D. thesis, MIT, Cambridge, MA, USA (2004)

Cavallaro, L., Saxena, P., Sekar, R.: On the limits of information flow techniques for malware analysis and containment. In: Zamboni, D. (ed.) DIMVA 2008. LNCS, vol. 5137, pp. 143–163. Springer, Heidelberg (2008) CrossRef

Cheney, J., Chiticariu, L., Tan, W.C.: Provenance in databases: why, how, and where. Found. Trends Databases 1(4), 379–474 (2009)CrossRef

Clause, J., Li, W., Orso, A.: Dytan: a generic dynamic taint analysis framework. In: Proceedings of ISSTA 2007, London, UK (2007)

Costa, M., Crowcroft, J., Castro, M., Rowstron, A., Zhou, L., Zhang, L., Barham, P.: Vigilante: end-to-end containment of internet worm epidemics. ACM TOCS 26(4), 1–68 (2008)CrossRef

Crandall, J.R., Chong, F.T.: Minos: control data attack prevention orthogonal to memory model. In: Proceedings of MICRO 37, Portland, OR, USA (2004)

Davidson, S.B., Freire, J.: Provenance and scientific workflows: challenges and opportunities. In: Proceedings of SIGMOD 2008, Vancouver, Canada (2008)

10.

Denning, D.E., Denning, P.J.: Certification of programs for secure information flow. Commun. ACM 20(7), 504–513 (1977)MATHCrossRef

11.

Freire, J.-L., Silva, C.T., Callahan, S.P., Santos, E., Scheidegger, C.E., Vo, H.T.: Managing rapidly-evolving scientific workflows. In: Moreau, L., Foster, I. (eds.) IPAW 2006. LNCS, vol. 4145, pp. 10–18. Springer, Heidelberg (2006) CrossRef

12.

Frew, J., Metzger, D., Slaughter, P.: Automatic capture and reconstruction of computational provenance. Concurr. Comput. Pract. Exper. 20(5), 485–496 (2008)CrossRef

13.

Gessiou, E., Pappas, V., Athanasopoulos, E., Keromytis, A.D., Ioannidis, S.: Towards a universal data provenance framework using dynamic instrumentation. In: Gritzalis, D., Furnell, S., Theoharidou, M. (eds.) SEC 2012. IFIP AICT, vol. 376, pp. 103–114. Springer, Heidelberg (2012) CrossRef

14.

Holland, D.A., Seltzer, M.I., Braun, U., Muniswamy-Reddy, K.K.: PASSing the provenance challenge. Concurr. Comput. Pract. Exper. 20(5), 531–540 (2008)CrossRef

15.

Kang, M.G., McCamant, S., Poosankam, P., Song, D.: DTA++: dynamic taint analysis with targeted control-flow propagation. In: Proceedings of NDSS 2011, San Diego, CA, USA (2011)

16.

Kemerlis, V.P., Portokalidis, G., Jee, K., Keromytis, A.D.: libdft: Practical dynamic data flow tracking for commodity systems. In: Proceedings of VEE 2012, London, UK (2012)

17.

Kim, J., Deelman, E., Gil, Y., Mehta, G., Ratnakar, V.: Provenance trails in the wings-pegasus system. Concurr. Comput. Pract. Exper. 20(5), 587–597 (2008)CrossRef

18.

Lattner, C., Adve, V.: LLVM: a compilation framework for lifelong program analysis & transformation. In: Proceedings of CGO 2004, Palo Alto, CA, USA (2004)

19.

Luk, C.K., Cohn, R., Muth, R., Patil, H., Klauser, A., Lowney, G., Wallace, S., Reddi, V.J., Hazelwood, K.: Pin: building customized program analysis tools with dynamic instrumentation. In: Proceedings of PLDI 2005, Chicago, IL, USA (2005)

20.

Macko, P., Seltzer, M.: A General-purpose provenance library. In: Proceedings of USENIX TaPP 2012, Boston, MA, USA (2012)

21.

Magliacane, S.: Reconstructing provenance. In: Cudré-Mauroux, P., et al. (eds.) ISWC 2012, Part II. LNCS, vol. 7650, pp. 399–406. Springer, Heidelberg (2012) CrossRef

22.

McCamant, S., Ernst, M.D.: Quantitative information-flow tracking for C and related languages. Technical report, MIT-CSAIL-TR-2006-076, MIT, Cambridge, MA, USA (2006)

23.

Miles, S., Groth, P., Munroe, S., Moreau, L.: PrIMe: a methodology for developing provenance-aware applications. ACM TOSEM 20(3), 8:1–8:42 (2009)

24.

Moreau, L.: The foundations for provenance on the web. Found. Trends Web Sci. 2(2–3), 99–241 (2010)MathSciNetCrossRef

25.

Moreau, L., Groth, P.: Provenance: an introduction to PROV. Synth. Lect. Semant. Web: Theory Technol. 3(4) (2013)

26.

Moreau, L., Missier, P.: PROV-DM: The PROV Data Model. Recommendation REC-prov-dm-20130430, W3C (2013)

27.

Nethercote, N., Seward, J.: Valgrind: a framework for heavyweight dynamic binary instrumentation. In: Proceedings of PLDI 2007, San Diego, CA, USA (2007)

28.

De Nies, T., Coppens, S., Van Deursen, D., Mannens, E., Van de Walle, R.: Automatic discovery of high-level provenance using semantic similarity. In: Groth, P., Frew, J. (eds.) IPAW 2012. LNCS, vol. 7525, pp. 97–110. Springer, Heidelberg (2012) CrossRef

29.

Oinn, T., Greenwood, M., et al.: Taverna: lessons in creating a workflow environment for the life sciences. Concurr. Comput. Pract. Exper. 18(10), 1067–1100 (2006)CrossRef

30.

Simmhan, Y.L., Plale, B., Gannon, D.: A survey of data provenance in e-science. SIGMOD Rec. 34(3), 31–36 (2005)CrossRef

31.

Simmhan, Y.L., Plale, B., Gannon, D.: Karma2: provenance management for data driven workflows. Int. J. Web Serv. Res. 5(2), 1–22 (2008)CrossRef

32.

Slowinska, A., Bos, H.: Pointless tainting?: evaluating the practicality of pointer tainting. In: Proceedings of EuroSys 2009, Nuremberg, Germany (2009)

33.

Srivastava, A., Eustace, A.: ATOM: a system for building customized program analysis tools. In: Proceedings of PLDI 1994, Orlando, FL, USA (1994)

34.

Vahdat, A., Anderson, T.: Transparent result caching. In: Proceedings of USENIX ATC 1998, New Orleans, LA, USA (1998)

35.

Widom, J.: Trio a system for data uncertainty and lineage. In: Aggarwal, C.C. (ed.) Managing and Mining Uncertain Data, vol. 35. Springer, New York (2009)

Titel: Looking Inside the Black-Box: Capturing Data Provenance Using Dynamic Instrumentation
verfasst von: Manolis Stamatogiannakis
Paul Groth
Herbert Bos
Verlag: Springer International Publishing
Buch: Provenance and Annotation of Data and Processes
Print ISBN: 978-3-319-16461-8

Electronic ISBN: 978-3-319-16462-5

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-16462-5_12

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"