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On differentially private inductive logic programming

Publication ,  Journal Article
Zeng, C; Lantz, E; Naughton, JF; Page, D
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2014

We consider differentially private inductive logic programming. We begin by formulating the problem of guarantee differential privacy to inductive logic programming, and then prove the theoretical difficulty of simultaneously providing good utility and good privacy in this task. While our analysis proves that in general this is very difficult, it leaves a glimmer of hope in that when the size of the training data is large or the search tree for hypotheses is “short” and “narrow,” we might be able to get meaningful results. To prove our intuition, we implement a differentially private version of Aleph, and our experimental results show that our algorithm is able to produce accurate results for those two cases.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2014

Volume

8812

Start / End Page

18 / 30

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Zeng, C., Lantz, E., Naughton, J. F., & Page, D. (2014). On differentially private inductive logic programming. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8812, 18–30. https://doi.org/10.1007/978-3-662-44923-3_2
Zeng, C., E. Lantz, J. F. Naughton, and D. Page. “On differentially private inductive logic programming.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8812 (January 1, 2014): 18–30. https://doi.org/10.1007/978-3-662-44923-3_2.
Zeng C, Lantz E, Naughton JF, Page D. On differentially private inductive logic programming. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2014 Jan 1;8812:18–30.
Zeng, C., et al. “On differentially private inductive logic programming.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8812, Jan. 2014, pp. 18–30. Scopus, doi:10.1007/978-3-662-44923-3_2.
Zeng C, Lantz E, Naughton JF, Page D. On differentially private inductive logic programming. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2014 Jan 1;8812:18–30.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2014

Volume

8812

Start / End Page

18 / 30

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences