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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 2 (February 2026).... Submit articles

Reviewing advancements in privacy-enhancing technologies for big data analytics in an era of increased surveillance

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  • Reviewing advancements in privacy-enhancing technologies for big data analytics in an era of increased surveillance

Olakunle Abayomi Ajala 1, Chuka Anthony Arinze 2, Onyeka Chrisanctus Ofodile 3, Chinwe Chinazo Okoye 4, and Obinna Donald Daraojimba 5, *

1 Indiana Wesleyan University, USA.
2 Independent Researcher, Port Harcourt, Rivers State, Nigeria.
3 Sanctus Maris Concepts, Nigeria Ltd.
4 Access Bank Plc, Nigeria.
5 Department of Information Management, Ahmadu Bello University, Zaria, Nigeria.

Review Article
 
World Journal of Advanced Engineering Technology and Sciences, 2024, 11(01), 294–300.
Article DOI: 10.30574/wjaets.2024.11.1.0060
DOI url: https://doi.org/10.30574/wjaets.2024.11.1.0060

Received on 08 January 2024; revised on 15 February 2024; accepted on 17 February 2024

In the contemporary landscape of big data analytics, privacy concerns loom large, exacerbated by escalating surveillance measures. This review delves into the advancements of privacy-enhancing technologies (PETs) amidst this era of heightened scrutiny. The review explores the evolving landscape of PETs, highlighting their pivotal role in safeguarding individual privacy while enabling meaningful data analysis. Firstly, the review elucidates the escalating surveillance environment, characterized by ubiquitous data collection practices and the proliferation of sophisticated monitoring mechanisms. Against this backdrop, the imperative for robust privacy solutions becomes evident. Subsequently, the review navigates through the array of PETs, encompassing differential privacy, homomorphic encryption, secure multi-party computation, and federated learning, among others. Each technology is scrutinized for its efficacy in mitigating privacy risks without compromising analytical utility. Furthermore, the review delineates notable applications of PETs across diverse domains, including healthcare, finance, and social media. Case studies exemplify how PETs facilitate data sharing and collaborative analysis while preserving confidentiality and compliance with regulatory frameworks. Moreover, the review examines the challenges hindering the widespread adoption of PETs, such as computational overhead, interoperability issues, and regulatory ambiguities. Strategies for overcoming these hurdles are elucidated, encompassing advancements in algorithmic efficiency, standardization efforts, and policy advocacy. The review underscores the pivotal role of PETs in reconciling the imperatives of data analytics with the imperatives of privacy protection amidst escalating surveillance. It emphasizes the necessity for interdisciplinary collaboration among researchers, policymakers, and industry stakeholders to foster the development and deployment of effective PET solutions, thereby ensuring a harmonious balance between data utility and individual privacy rights in the digital age.

Big Data; Analytics; Surveillance; Technology; Privacy-Enhanced; Review

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2024-0060.pdf

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Olakunle Abayomi Ajala, Chuka Anthony Arinze, Onyeka Chrisanctus Ofodile, Chinwe Chinazo Okoye and Obinna Donald Daraojimba. Reviewing advancements in privacy-enhancing technologies for big data analytics in an era of increased surveillance. World Journal of Advanced Engineering Technology and Sciences, 2024, 11(01), 294–300. Article DOI: https://doi.org/10.30574/wjaets.2024.11.1.0060

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