Privacy preservation of social network users against attribute inference attacks via malicious data mining

Khondker Jahid Reza; M. Zahidul Islam; Vladimir Estivill-Castro

doi:10.5220/0007390404120420

Privacy preservation of social network users against attribute inference attacks via malicious data mining

Khondker Jahid Reza, M. Zahidul Islam, Vladimir Estivill-Castro

DTIC Universitat Pompeu Fabra

Research output: Book chapter/Published conference paper › Conference paper › peer-review

10 Citations (Scopus)

42 Downloads (Pure)

Abstract

Online social networks (OSNs) are currently a popular platform for social interactions among people. Usually, OSN users upload various contents including personal information on their profiles. The ability to infer users' hidden information or information that has not been even uploaded (i.e. private/sensitive information) by an unauthorised agent is commonly known as attribute inference problem. In this paper, we propose 3LP+, a privacy-preserving technique, to protect users' sensitive information leakage. We apply 3LP+ on a synthetically generated OSN data set and demonstrate the superiority of 3LP+ over an existing privacy-preserving technique.

Original language	English
Title of host publication	Proceedings of the 5th International Conference on Information Systems Security and Privacy
Subtitle of host publication	ICISSP 2019
Editors	Paolo Mori, Olivier Camp, Steven Furnell
Publisher	Scitepress
Pages	412-420
Number of pages	9
ISBN (Electronic)	9789897583599
DOIs	https://doi.org/10.5220/0007390404120420
Publication status	Published - 23 Feb 2019
Event	5th International Conference on Information Systems Security and Privacy: ICISSP 2019 - Vienna House Diplomat Prague, Prague, Czech Republic Duration: 23 Feb 2019 → 25 Feb 2019 https://icissp.scitevents.org/?y=2019 (Conference website) https://www.scitepress.org/ProceedingsDetails.aspx?ID=2JXfLZNuB94=&t=1 (proceedings) http://www.icissp.org/CallForPapers.aspx?y=2019 (call for papers) https://www.springer.com/gp/book/9783030494421 (Proceedings (Springer publication))

Publication series

Name	ICISSP 2019 - Proceedings of the 5th International Conference on Information Systems Security and Privacy

Conference

Conference	5th International Conference on Information Systems Security and Privacy
Country/Territory	Czech Republic
City	Prague
Period	23/02/19 → 25/02/19
Other	The International Conference on Information Systems Security and Privacy aims at creating a meeting point for researchers and practitioners that address security and privacy challenges that concern information systems, especially in organizations, including not only technological issues but also social issues. The conference welcomes papers of either practical or theoretical nature, presenting research or applications addressing all aspects of security and privacy, that concerns to organizations and individuals, thus creating new research opportunities.
Internet address	https://icissp.scitevents.org/?y=2019 (Conference website) https://www.scitepress.org/ProceedingsDetails.aspx?ID=2JXfLZNuB94=&t=1 (proceedings) http://www.icissp.org/CallForPapers.aspx?y=2019 (call for papers) https://www.springer.com/gp/book/9783030494421 (Proceedings (Springer publication))

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Cite this

Reza, K. J., Islam, M. Z., & Estivill-Castro, V. (2019). Privacy preservation of social network users against attribute inference attacks via malicious data mining. In P. Mori, O. Camp, & S. Furnell (Eds.), Proceedings of the 5th International Conference on Information Systems Security and Privacy: ICISSP 2019 (pp. 412-420). (ICISSP 2019 - Proceedings of the 5th International Conference on Information Systems Security and Privacy). Scitepress. https://doi.org/10.5220/0007390404120420

Reza, Khondker Jahid ; Islam, M. Zahidul ; Estivill-Castro, Vladimir. / Privacy preservation of social network users against attribute inference attacks via malicious data mining. Proceedings of the 5th International Conference on Information Systems Security and Privacy: ICISSP 2019. editor / Paolo Mori ; Olivier Camp ; Steven Furnell. Scitepress, 2019. pp. 412-420 (ICISSP 2019 - Proceedings of the 5th International Conference on Information Systems Security and Privacy).

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title = "Privacy preservation of social network users against attribute inference attacks via malicious data mining",

abstract = "Online social networks (OSNs) are currently a popular platform for social interactions among people. Usually, OSN users upload various contents including personal information on their profiles. The ability to infer users' hidden information or information that has not been even uploaded (i.e. private/sensitive information) by an unauthorised agent is commonly known as attribute inference problem. In this paper, we propose 3LP+, a privacy-preserving technique, to protect users' sensitive information leakage. We apply 3LP+ on a synthetically generated OSN data set and demonstrate the superiority of 3LP+ over an existing privacy-preserving technique.",

keywords = "Attribute Inference, Data Mining, Privacy Protection Technique",

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note = "Includes bibliographical references.; 5th International Conference on Information Systems Security and Privacy : ICISSP 2019 ; Conference date: 23-02-2019 Through 25-02-2019",

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Reza, KJ, Islam, MZ & Estivill-Castro, V 2019, Privacy preservation of social network users against attribute inference attacks via malicious data mining. in P Mori, O Camp & S Furnell (eds), Proceedings of the 5th International Conference on Information Systems Security and Privacy: ICISSP 2019. ICISSP 2019 - Proceedings of the 5th International Conference on Information Systems Security and Privacy, Scitepress, pp. 412-420, 5th International Conference on Information Systems Security and Privacy, Prague, Czech Republic, 23/02/19. https://doi.org/10.5220/0007390404120420

Privacy preservation of social network users against attribute inference attacks via malicious data mining. / Reza, Khondker Jahid; Islam, M. Zahidul; Estivill-Castro, Vladimir.
Proceedings of the 5th International Conference on Information Systems Security and Privacy: ICISSP 2019. ed. / Paolo Mori; Olivier Camp; Steven Furnell. Scitepress, 2019. p. 412-420 (ICISSP 2019 - Proceedings of the 5th International Conference on Information Systems Security and Privacy).

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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T1 - Privacy preservation of social network users against attribute inference attacks via malicious data mining

AU - Reza, Khondker Jahid

AU - Islam, M. Zahidul

AU - Estivill-Castro, Vladimir

N1 - Includes bibliographical references.

PY - 2019/2/23

Y1 - 2019/2/23

N2 - Online social networks (OSNs) are currently a popular platform for social interactions among people. Usually, OSN users upload various contents including personal information on their profiles. The ability to infer users' hidden information or information that has not been even uploaded (i.e. private/sensitive information) by an unauthorised agent is commonly known as attribute inference problem. In this paper, we propose 3LP+, a privacy-preserving technique, to protect users' sensitive information leakage. We apply 3LP+ on a synthetically generated OSN data set and demonstrate the superiority of 3LP+ over an existing privacy-preserving technique.

AB - Online social networks (OSNs) are currently a popular platform for social interactions among people. Usually, OSN users upload various contents including personal information on their profiles. The ability to infer users' hidden information or information that has not been even uploaded (i.e. private/sensitive information) by an unauthorised agent is commonly known as attribute inference problem. In this paper, we propose 3LP+, a privacy-preserving technique, to protect users' sensitive information leakage. We apply 3LP+ on a synthetically generated OSN data set and demonstrate the superiority of 3LP+ over an existing privacy-preserving technique.

KW - Attribute Inference

KW - Data Mining

KW - Privacy Protection Technique

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Reza KJ, Islam MZ, Estivill-Castro V. Privacy preservation of social network users against attribute inference attacks via malicious data mining. In Mori P, Camp O, Furnell S, editors, Proceedings of the 5th International Conference on Information Systems Security and Privacy: ICISSP 2019. Scitepress. 2019. p. 412-420. (ICISSP 2019 - Proceedings of the 5th International Conference on Information Systems Security and Privacy). doi: 10.5220/0007390404120420

Privacy preservation of social network users against attribute inference attacks via malicious data mining

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