De-Identification of Unstructured Textual Data using Artificial Immune System for Privacy Preserving

Amine Rahmani, Abdelmalek Amine, Reda Mohamed Hamou, Mohamed Amine Boudia and Hadj Ahmed Bouarara
Additional contact information
Amine Rahmani: Department of Computer Science, Dr. Tahar Moulay University of Saida, Saida, Algeria
Abdelmalek Amine: Department of Computer Science, Dr. Tahar Moulay University of Saida, Saida, Algeria
Reda Mohamed Hamou: Department of Computer Science, Dr. Tahar Moulay University of Saida, Saida, Algeria
Mohamed Amine Boudia: Department of Computer Science, Dr. Tahar Moulay University of Saida, Saida, Algeria
Hadj Ahmed Bouarara: GeCoDe laboratory, Department of Computer Sciences, Dr. Tahar Moulay University of Saida, Algeria

International Journal of Decision Support System Technology (IJDSST), 2016, vol. 8, issue 4, 34-49

Abstract: The development of new technologies has led the world into a tipping point. One of these technologies is the big data which made the revolution of computer sciences. Big data has come with new challenges. These challenges can be resumed in the aim of creating scalable and efficient services that can treat huge amounts of heterogeneous data in small scale of time while preserving users' privacy. Textual data occupy a wide space in internet. These data could contain information that can lead to identify users. For that, the development of such approaches that can detect and remove any identifiable information has become a critical research area known as de-identification. This paper tackle the problem of privacy in textual data. The authors' proposed approach consists of using artificial immune systems and MapReduce to detect and hide identifiable words with no matter on their variants using the personnel information of the user from his profile. After many experiments, the system shows a high efficiency in term of number of detected words, the way they are hided with, and time of execution.

Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJDSST.2016100103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jdsst0:v:8:y:2016:i:4:p:34-49

Access Statistics for this article

International Journal of Decision Support System Technology (IJDSST) is currently edited by Shaofeng Liu

More articles in International Journal of Decision Support System Technology (IJDSST) from IGI Global
Bibliographic data for series maintained by Journal Editor ().