Provenance in Databases: Why, How, and Where

Cheney, James; Chiticariu, Laura; Tan, Wang-Chiew

doi:10.1561/1900000006

Cited by 401 publications

(294 citation statements)

References 44 publications

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“…Provenance has been widely studied in the database [5], distributed systems [31] and e-science communities [9]. For a comprehensive overview of the field, we refer the reader to Moreau [24].…”

Section: Capturing Provenancementioning

confidence: 99%

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

Stamatogiannakis¹,

Groth²,

Bos³

2015

Lecture Notes in Computer Science

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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.

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Section: Capturing Provenancementioning

confidence: 99%

“…For a comprehensive overview of the field, we refer the reader to Moreau [24]. Furthermore, Cheney et al [5] and Simmhan et al [30] provide specialized reviews for databases and e-science respectively. Here, we focus on systems for provenance capture.…”

Section: Capturing Provenancementioning

confidence: 99%

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

Stamatogiannakis¹,

Groth²,

Bos³

2015

Lecture Notes in Computer Science

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“…Provenance information is crucial for many applications, from data quality and aggregation to trust, and it has been researched from several perspectives (see surveys [9,12,20]). …”

Section: Problem Statementmentioning

confidence: 99%

Reconstructing Provenance

Magliacane¹

2012

The Semantic Web – ISWC 2012

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Abstract. Provenance is an increasingly important aspect of data management that is often underestimated and neglected by practitioners. In our work, we target the problem of reconstructing provenance of files in a shared folder setting, assuming that only standard filesystem metadata are available. We propose a content-based approach that is able to reconstruct provenance automatically, leveraging several similarity measures and edit distance algorithms, adapting and integrating them into a multi-signal pipeline. We discuss our research methodology and show some promising preliminary results.

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“…This makes it easier to compare, relate and generalize these approaches, though such comparisons are only starting to appear [13], [29]. For most of these models, there are semantic guarantees (or even exact semantic characterizations) relating the provenance records to the denotation of the program.…”

Section: Related and Future Workmentioning

confidence: 99%

A Formal Framework for Provenance Security

Cheney

2011

2011 IEEE 24th Computer Security Foundations Symposium

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Abstract-Provenance, or information about the origin, derivation, or history of data, is becoming an important topic especially for shared scientific or public data on the Web. It clearly has implications on security (and vice versa) yet these implications are not well-understood. A great deal of work has focused on mechanisms for recording, managing or using some kind of provenance information, but relatively little progress has been made on foundational models that define provenance and relate it to security goals such as availability, confidentiality or privacy. We argue that such foundations are essential to making meaningful progress on these problems and should be developed. In this paper, we outline a formal model of provenance, propose formalizations of security properties for provenance such as disclosure and obfuscation, and explore their implications in domains based on automata, database queries and workflow provenance graphs.

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Provenance in Databases: Why, How, and Where

Cited by 401 publications

References 44 publications

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

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

Reconstructing Provenance

A Formal Framework for Provenance Security

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