On the Computational Complexities of Three Privacy Measures for - - PowerPoint PPT Presentation

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On the Computational Complexities of Three Privacy Measures for - - PowerPoint PPT Presentation

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On the Computational Complexities of Three Privacy Measures for Large Networks Under Active Attack Bhaskar DasGupta Department of Computer Science University of Illinois at Chicago Chicago, IL 60607, USA dasgupta@cs.uic.edu

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On the Computational Complexities of Three Privacy Measures for Large Networks Under Active Attack

Bhaskar DasGupta Department of Computer Science University of Illinois at Chicago Chicago, IL 60607, USA dasgupta@cs.uic.edu http://www.cs.uic.edu/~dasgupta Bases on joint work with

  • T. Chatterjee, N. Mobasheri, V. Srinivasan and I. Yero

Supported by NSF grant IIS-1160995

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Network Privacy Under Active Attack

(privacy loving) Users nodes infected by malicious attackers malicious attackers are interested in sensitive attributes such as

  • node degrees
  • inter-node distances
  • connecitivity of network
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identifying the “relevant attribute” (for this talk) distance vector from attacked nodes

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Related Prior Concepts

  • Metric dimension (also called landmarks)

Distance vectors must be mutually non-identical [Harary & Melter; 1976] [Khuller, Raghavachari & Rosenfeld; 1996] [Hauptmann, Schmied & Viehmann; 2012] Similar in flavor to general set cover problem

  • Strong metric dimension

Constrained distance vectors [Oellermann & Peters-Fransen; 2012] [DasGupta & Mobasheri; 2017] Similar in flavor to the node cover problem

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Other known privacy computational models and concepts

  • Multi-party communication context

– [Yao, 1979], [Kushilevitz, 1992]

  • Geometric notions of privacy

– [Feigenbaum, Jaggard, Schapira, 2010], [Comi, DasGupta, Schapira, Srinivasan, 2012]

  • Information-theoretic

– [Bar-Yehuda, Chor, Kushilevitz, Orlitsky, 1993]

  • Differential privacy (database retrieval context)

– [Dwork, 2006]

  • Anonymization approach (like this talk)

– [Backstrom, Dwork, Kleinberg, 2007]

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n is number of nodes

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n is number of nodes

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to be discussed next

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k=1

n is number of nodes

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