Secure Data Management Life Cycle for Government Big-Data Ecosystem: Design and Development Perspective

Author:

Zahid Reeba1,Altaf Ayesha1ORCID,Ahmad Tauqir1,Iqbal Faiza1ORCID,Vera Yini Airet Miró2345ORCID,Flores Miguel Angel López267ORCID,Ashraf Imran8ORCID

Affiliation:

1. Department of Computer Science, University of Engineering & Technology, (UET), Lahore P.O. Box No. 54890, Pakistan

2. Research Group on Foods, Universidad Europea del Atlántico, Isabel Torres 21, 39011 Santander, Spain

3. Research Group on Foods, Universidad Internacional Iberoamericana, Arecibo, PR 00613, USA

4. Department of Project Management, Universidade Internacional do Cuanza, Cuito EN250, Bie, Angola

5. Fundación Universitaria Internacional de Colombia, Bogota 111311, Colombia

6. Department of Project Management, Universidad Internacional Iberoamericana, Campeche 24560, Mexico

7. Instituto Politécnico Nacional, UPIICSA, Mexico City 04510, Mexico

8. Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea

Abstract

The rapid generation of data from various sources by the public sector, private corporations, business associations, and local communities is referred to as big data. This large and complex dataset is often regarded as the ‘new oil’ by public administrations (PAs), and data-driven approaches are employed to transform it into valuable insights that can improve governance, transparency, digital services, and public engagement. The government’s big-data ecosystem (GBDE) is a result of this initiative. Effective data management is the first step towards large-scale data analysis, which yields insights that benefit your work and your customers. However, managing big data throughout its life cycle is a daunting challenge for public agencies. Despite its widespread use, big data management is still a significant obstacle. To address this issue, this study proposes a hybrid approach to secure the data management life cycle for GBDE. Specifically, we use a combination of the ECC algorithm with AES 128 BITS encryption to ensure that the data remain confidential and secure. We identified and analyzed various data life cycle models through a systematic literature review to create a data management life cycle for data-driven governments. This approach enhances the security and privacy of data management and addresses the challenges faced by public agencies.

Funder

European University of Atlantic

Publisher

MDPI AG

Subject

Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software

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