Incorporating Privacy by Design Principles in the Modification of AI Systems in Preventing Breaches across Multiple Environments, Including Public Cloud, Private Cloud, and On-prem

23 Pages Posted: 7 Oct 2024

See all articles by Samuel Ufom Okon

Samuel Ufom Okon

First Bank of Nigeria

Omobolaji Olateju

University of Ibadan - Department of Chemistry

Olumide Samuel Ogungbemi

Centennial College

Sunday Joseph

Ashland University

Anthony Obulor Olisa

University Of Cumberlands

Oluwaseun Oladeji Olaniyi

University of the Cumberlands

Date Written: September 03, 2024

Abstract

The rapid integration of artificial intelligence (AI) across various sectors has significantly amplified privacy concerns, particularly with the growing reliance on cloud environments. Existing methods often fall short of effectively preventing privacy breaches due to inadequate risk assessment and mitigation strategies. These limitations highlight the necessity for more robust solutions, indicating the importance of Privacy by Design (PbD) principles. This study addresses these gaps by proposing a comprehensive approach to incorporating PbD principles into AI systems to prevent breaches across public, private, and on-prem environments. The proposed work utilizes logistic regression analysis to identify significant predictors of privacy breaches, revealing that both the environment (B =-1.142, p < .001) and severity of vulnerabilities (B = 0.932, p < .01) play crucial roles. Additionally, a strong positive correlation (r = 0.791) between breach detection rates and PbD effectiveness is observed, indicating the need for enhanced detection mechanisms. To support the empirical findings, this study also reviews existing case studies. It conducts a thematic analysis to provide a deeper understanding of the practical challenges and solutions associated with PbD implementation, particularly in healthcare and smart city applications. These analyses serve to supplement the empirical evidence and demonstrate the effectiveness of PbD over other existing methods. The study concludes that implementing PbD principles is critical for achieving robust privacy protection, and the study recommends prioritizing advanced breach detection mechanisms, comprehensive privacy impact assessments, continuous stakeholder engagement, and investment in privacy-enhancing technologies to address privacy risks effectively.

Keywords: Privacy by design, AI systems, privacy breaches, breach detection, privacy-enhancing technologies

Suggested Citation

Okon, Samuel Ufom and Olateju, Omobolaji and Ogungbemi, Olumide Samuel and Joseph, Sunday Abayomi and Olisa, Anthony Obulor and Olaniyi, Oluwaseun Oladeji, Incorporating Privacy by Design Principles in the Modification of AI Systems in Preventing Breaches across Multiple Environments, Including Public Cloud, Private Cloud, and On-prem (September 03, 2024). Available at SSRN: https://ssrn.com/abstract=4945564 or http://dx.doi.org/10.2139/ssrn.4945564

Samuel Ufom Okon

First Bank of Nigeria ( email )

Omobolaji Olateju

University of Ibadan - Department of Chemistry ( email )

Olumide Samuel Ogungbemi

Centennial College ( email )

Sunday Abayomi Joseph

Ashland University ( email )

401 College Avenue
Ashland, OH Ashland 44805
United States

Anthony Obulor Olisa

University Of Cumberlands ( email )

Oluwaseun Oladeji Olaniyi (Contact Author)

University of the Cumberlands ( email )

6178 College Station Drive
Williamsburg, KY 40769
United States

HOME PAGE: http://www.ucumberlands.edu

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