JPrivacy: A Java Privacy Profiling Framework for Big Data Applications

Mohamed Abdellatif; Iman Saleh; M.Brian Blake

1st International Workshop on Collaborative Big Data

Research Article

JPrivacy: A Java Privacy Profiling Framework for Big Data Applications

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Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/icst.collaboratecom.2014.257666,
    author={Mohamed Abdellatif and Iman Saleh and M.Brian Blake},
    title={JPrivacy: A Java Privacy Profiling Framework for Big Data Applications},
    proceedings={1st International Workshop on Collaborative Big Data},
    publisher={IEEE},
    proceedings_a={C-BIG},
    year={2014},
    month={11},
    keywords={privacy big data java static analysis},
    doi={10.4108/icst.collaboratecom.2014.257666}
}

Mohamed Abdellatif
Iman Saleh
M.Brian Blake
Year: 2014
JPrivacy: A Java Privacy Profiling Framework for Big Data Applications
C-BIG
ICST
DOI: 10.4108/icst.collaboratecom.2014.257666

Mohamed Abdellatif¹, Iman Saleh¹^,*, M.Brian Blake¹

1: University of Miami

*Contact email: iman@miami.edu

Abstract

Businesses and government agencies are continuously generating and collecting huge amounts of data and building related Big Data applications. Big Data applications involve the collaborative integration of APIs from different providers. A challenge in this domain is to guarantee the conformance of the integration to privacy terms and regulations. In this paper, we present JPrivacy, a privacy profiling framework for Big Data applications. JPrivacy proposes a model for privacy rules and provide the algorithms and related tools to check Java code against these rules. We show through experimentation that JPrivacy can effectively detect privacy violations by statically analyzing a piece of code.

Keywords: privacy big data java static analysis

Published: 2014-11-11
Publisher: IEEE

: http://dx.doi.org/10.4108/icst.collaboratecom.2014.257666