A Constraint-Based Model for the Frequent Itemset Hiding Problem

Vassilios S. Verykios; Elias C. Stavropoulos; Vasilis Zorkadis; Ahmed K. Elmagarmid

doi:10.1007/978-3-030-37545-4_4

A Constraint-Based Model for the Frequent Itemset Hiding Problem

Vassilios S. Verykios, Elias C. Stavropoulos^*, Vasilis Zorkadis, Ahmed K. Elmagarmid

^*Corresponding author for this work

Qatar Computing Research Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

This paper introduces a novel constraint-based hiding model to drastically reduce the preprocessing overhead that is incurred by border-based techniques in the hiding of sensitive frequent itemsets. The proposed model is solved by an efficient constraint-based mining algorithm that pushes a conjunction of antimonotone constraints into an Apriori-like algorithm, for inducing the support theory of non-sensitive frequent itemsets along with its negative border. The patterns induced by the constraint-based mining algorithm can be used in border-based hiding algorithms to construct a sanitized version of the original database, where the sensitive knowledge is concealed. The efficiency of the constraint-based mining algorithm is evaluated on real and synthetic datasets.

Original language	English
Title of host publication	E-Democracy – Safeguarding Democracy and Human Rights in the Digital Age - 8th International Conference, e-Democracy 2019, Proceedings
Editors	Sokratis Katsikas, Sokratis Katsikas, Vasilios Zorkadis
Publisher	Springer
Pages	49-64
Number of pages	16
ISBN (Print)	9783030375447
DOIs	https://doi.org/10.1007/978-3-030-37545-4_4
Publication status	Published - 2020
Event	8th e-Democracy International Conference on Safeguarding Democracy and Human Rights in the Digital Age, e-Democracy 2019 - Athens, Greece Duration: 12 Dec 2019 → 13 Dec 2019

Publication series

Name	Communications in Computer and Information Science
Volume	1111 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	8th e-Democracy International Conference on Safeguarding Democracy and Human Rights in the Digital Age, e-Democracy 2019
Country/Territory	Greece
City	Athens
Period	12/12/19 → 13/12/19

Keywords

Constraint-based data mining
Frequent itemset hiding
Knowledge hiding
Linear programming
Privacy Preserving Data Mining

Access to Document

10.1007/978-3-030-37545-4_4

Cite this

Verykios, V. S., Stavropoulos, E. C., Zorkadis, V., & Elmagarmid, A. K. (2020). A Constraint-Based Model for the Frequent Itemset Hiding Problem. In S. Katsikas, S. Katsikas, & V. Zorkadis (Eds.), E-Democracy – Safeguarding Democracy and Human Rights in the Digital Age - 8th International Conference, e-Democracy 2019, Proceedings (pp. 49-64). (Communications in Computer and Information Science; Vol. 1111 CCIS). Springer. https://doi.org/10.1007/978-3-030-37545-4_4

Verykios, Vassilios S. ; Stavropoulos, Elias C. ; Zorkadis, Vasilis et al. / A Constraint-Based Model for the Frequent Itemset Hiding Problem. E-Democracy – Safeguarding Democracy and Human Rights in the Digital Age - 8th International Conference, e-Democracy 2019, Proceedings. editor / Sokratis Katsikas ; Sokratis Katsikas ; Vasilios Zorkadis. Springer, 2020. pp. 49-64 (Communications in Computer and Information Science).

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abstract = "This paper introduces a novel constraint-based hiding model to drastically reduce the preprocessing overhead that is incurred by border-based techniques in the hiding of sensitive frequent itemsets. The proposed model is solved by an efficient constraint-based mining algorithm that pushes a conjunction of antimonotone constraints into an Apriori-like algorithm, for inducing the support theory of non-sensitive frequent itemsets along with its negative border. The patterns induced by the constraint-based mining algorithm can be used in border-based hiding algorithms to construct a sanitized version of the original database, where the sensitive knowledge is concealed. The efficiency of the constraint-based mining algorithm is evaluated on real and synthetic datasets.",

keywords = "Constraint-based data mining, Frequent itemset hiding, Knowledge hiding, Linear programming, Privacy Preserving Data Mining",

author = "Verykios, {Vassilios S.} and Stavropoulos, {Elias C.} and Vasilis Zorkadis and Elmagarmid, {Ahmed K.}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 8th e-Democracy International Conference on Safeguarding Democracy and Human Rights in the Digital Age, e-Democracy 2019 ; Conference date: 12-12-2019 Through 13-12-2019",

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Verykios, VS, Stavropoulos, EC, Zorkadis, V & Elmagarmid, AK 2020, A Constraint-Based Model for the Frequent Itemset Hiding Problem. in S Katsikas, S Katsikas & V Zorkadis (eds), E-Democracy – Safeguarding Democracy and Human Rights in the Digital Age - 8th International Conference, e-Democracy 2019, Proceedings. Communications in Computer and Information Science, vol. 1111 CCIS, Springer, pp. 49-64, 8th e-Democracy International Conference on Safeguarding Democracy and Human Rights in the Digital Age, e-Democracy 2019, Athens, Greece, 12/12/19. https://doi.org/10.1007/978-3-030-37545-4_4

A Constraint-Based Model for the Frequent Itemset Hiding Problem. / Verykios, Vassilios S.; Stavropoulos, Elias C.; Zorkadis, Vasilis et al.
E-Democracy – Safeguarding Democracy and Human Rights in the Digital Age - 8th International Conference, e-Democracy 2019, Proceedings. ed. / Sokratis Katsikas; Sokratis Katsikas; Vasilios Zorkadis. Springer, 2020. p. 49-64 (Communications in Computer and Information Science; Vol. 1111 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Verykios, Vassilios S.

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AU - Zorkadis, Vasilis

AU - Elmagarmid, Ahmed K.

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

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AB - This paper introduces a novel constraint-based hiding model to drastically reduce the preprocessing overhead that is incurred by border-based techniques in the hiding of sensitive frequent itemsets. The proposed model is solved by an efficient constraint-based mining algorithm that pushes a conjunction of antimonotone constraints into an Apriori-like algorithm, for inducing the support theory of non-sensitive frequent itemsets along with its negative border. The patterns induced by the constraint-based mining algorithm can be used in border-based hiding algorithms to construct a sanitized version of the original database, where the sensitive knowledge is concealed. The efficiency of the constraint-based mining algorithm is evaluated on real and synthetic datasets.

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KW - Knowledge hiding

KW - Linear programming

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Verykios VS, Stavropoulos EC, Zorkadis V, Elmagarmid AK. A Constraint-Based Model for the Frequent Itemset Hiding Problem. In Katsikas S, Katsikas S, Zorkadis V, editors, E-Democracy – Safeguarding Democracy and Human Rights in the Digital Age - 8th International Conference, e-Democracy 2019, Proceedings. Springer. 2020. p. 49-64. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-37545-4_4

A Constraint-Based Model for the Frequent Itemset Hiding Problem

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