Privacy preserving big data analytics : A critical analysis of state-of-the-art

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

11 Scopus Citations
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Author(s)

  • M. Ileas Pramanik
  • Md Sakir Hossain
  • Md Mizanur Rahoman
  • Sumon Kumar Debnath
  • Md Golam Rashed
  • Md Zasim Uddin

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article numbere1387
Journal / PublicationWiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Online published7 Oct 2020
Publication statusOnline published - 7 Oct 2020

Abstract

In the era of "big data," a huge number of people, devices, and sensors are connected via digital networks and the cross-plays among these entities generate enormous valuable data that facilitate organizations to innovate and grow. However, the data deluge also raises serious privacy concerns which may cause a regulatory backlash and hinder further organizational innovation. To address the challenge of information privacy, researchers have explored privacy-preserving methodologies in the past two decades. However, a thorough study of privacy preserving big data analytics is missing in existing literature. The main contributions of this article include a systematic evaluation of various privacy preservation approaches and a critical analysis of the state-of-the-art privacy preserving big data analytics methodologies. More specifically, we propose a four-dimensional framework for analyzing and designing the next generation of privacy preserving big data analytics approaches. Besides, we contribute to pinpoint the potential opportunities and challenges of applying privacy preserving big data analytics to business settings. We provide five recommendations of effectively applying privacy-preserving big data analytics to businesses. To the best of our knowledge, this is the first systematic study about state-of-the-art in privacy-preserving big data analytics. The managerial implication of our study is that organizations can apply the results of our critical analysis to strengthen their strategic deployment of big data analytics in business settings, and hence to better leverage big data for sustainable organizational innovation and growth. This article is categorized under: Commercial, Legal, and Ethical Issues > Security and Privacy Fundamental Concepts of Data and Knowledge > Big Data Mining Fundamental Concepts of Data and Knowledge > Data Concepts

Research Area(s)

  • big data, business analytics, information privacy, privacy preservation, INFORMATION

Citation Format(s)

Privacy preserving big data analytics : A critical analysis of state-of-the-art. / Pramanik, M. Ileas; Lau, Raymond Y. K.; Hossain, Md Sakir; Rahoman, Md Mizanur; Debnath, Sumon Kumar; Rashed, Md Golam; Uddin, Md Zasim.

In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 07.10.2020.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review