Differential Securitization of Biometric Border Technologies in Kenya: Infrastructure, Border Type, and Uneven Control

This study advances a concept of differential securitization outcomes of biometric technologies used in detecting and mitigating immigration related crimes at border points. We argue that the site-systematic variation in biometric security performance is driven by unequal security infrastructure, porous physical perimeters, and differential officer capacity. Using a mixed-methods approach encompassing cross-sectional survey design across three purposively selected border control points: Jomo Kenyatta International Airport (JKIA), Busia, and Namanga One-Stop Border Control Points (OSBCP) in Kenya, data were collected using structured questionnaires administered to 670 travellers/passengers and 155 immigration officers yielding 59.7% and 71.4% response rates respectively, with the latter exceeding Babbie's (2010) 70% validity threshold. Data from respondents were supplemented by 60 structured observation sessions (27 at JKIA, 18 at Namanga, and 15 at Busia), interviews, and systematic document review. This study found that Kenya's biometric border modernisation programme has markedly different securitization outcomes across site types. At JKIA, biometric integration scores average 4.28 out of 5.0 and system uptime approaches 97% of working hours. At Namanga land border, the same technology achieves a 3.42 integration score and operates for only approximately 55% of working hours, producing a 42-percentage-point gap in effectiveness that is structurally produced, not incidental. Ordinary Least Squares (OLS) regression revealed that composite biometric effectiveness (B = 0.526, β = 0.594, t = 13.65, p < .001), infrastructure quality (β = 0.102, t = 2.55, p = .011), and border-point context (β = −0.084, t = −2.31, p = .021) together accounted for 47.2% of variance in threat mitigation outcomes (F(3,382) = 113.78, p < .001). Logistic regression identified infrastructure quality (OR = 8.94, 95% CI: 4.20–19.10), physical system integration (OR = 7.31, 95% CI: 3.50–15.20), and officer training (OR = 5.62, 95% CI: 2.80–11.30) as the dominant structural predictors of high-intensity securitization. Analysis of Variance (ANOVA) pointed to significant cross-site confidence gaps (F(2,382) = 34.2, p < .001) and chi-square analyses bore out divergence in officer confidence (χ²(2, N = 386) = 47.3, p < .001) and street-level practices (χ²(2, N = 386) = 21.82, p < .001). Differential securitization is a measurable governance phenomenon requiring targeted infrastructure investment, physical perimeter development, mandatory officer certification, and operationalisation of Kenya's Data Protection Act 2019 at border level.

Biometric border security; differential securitization; Kenya; border governance; securitization theory

1. Babbie, E. (2010). The practice of social research (12th ed.). Wadsworth. [Google Scholar] [Crossref]

2. Bhanye, J., & Shayamunda, M. (2025). Biometric systems at southern African land borders: Interoperability constraints and security outcomes. Journal of Border Security Studies, 4(1), 45–67. [Google Scholar] [Crossref]

3. Buzan, B., Waever, O., & de Wilde, J. (1998). Security: A new framework for analysis. Lynne Rienner. [Google Scholar] [Crossref]

4. Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE. [Google Scholar] [Crossref]

5. Emery, F. (1959). Characteristics of socio-technical systems. Tavistock Institute. [Google Scholar] [Crossref]

6. Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE. [Google Scholar] [Crossref]

7. International Organization for Migration. (2024). Africa migration report: Second edition. IOM. [Google Scholar] [Crossref]

8. Khan, S., & Efthymiou, E. (2021). Biometric border management in resource-constrained environments: Evidence from sub-Saharan Africa. International Journal of Migration and Border Studies, 7(3), 201–224. [Google Scholar] [Crossref]

9. Kloppenburg, S., & van der Ploeg, I. (2020). Securing identities: Biometric technologies and the enactment of human bodily differences. Science as Culture, 29(1), 57–76. [Google Scholar] [Crossref]

10. Madianou, M., Longman, L., & Ho, P. (2021). Biometric ID systems and humanitarian protection in sub-Saharan Africa: Technology, unreliability, and exclusion. Global Policy, 12(S6), 57–68. [Google Scholar] [Crossref]

11. Masua, R. (2026). Biometric surveillance and border security in Kenya: Opportunities, challenges and policy implications (Unpublished doctoral thesis). Kenyatta University. [Google Scholar] [Crossref]

12. Mlambo, V., Mlambo, K., & Kandiero, A. (2022). Border control effectiveness in Africa: Technology deployment and institutional constraints. African Security, 15(2), 141–163. [Google Scholar] [Crossref]

13. Muthaara, A.K. (2018). Effects of illegal migration in Africa: A case study of Kenya. MA Project, Institute of Diplomacy and International Studies, University of Nairobi, Kenya. [Google Scholar] [Crossref]

14. Murphy, K. (2004). The role of trust in nurturing compliance: A study of accused tax avoiders. Law and Human Behavior, 28(2), 187–209. [Google Scholar] [Crossref]

15. Pallant, J. (2020). SPSS survival manual (7th ed.). Open University Press. [Google Scholar] [Crossref]

16. Sunshine, J., & Tyler, T. (2003). The role of procedural justice and legitimacy in shaping public support for policing. Law and Society Review, 37(3), 513–548. [Google Scholar] [Crossref]

17. Trist, E., & Bamforth, K. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3–38. [Google Scholar] [Crossref]

18. Tyler, T. (1990). Why people obey the law. Yale University Press. [Google Scholar] [Crossref]

19. Waever, O. (1995). Securitization and desecuritization. In R. Lipschutz (Ed.), On security (pp. 46–86). Columbia University Press. [Google Scholar] [Crossref]

• Global Political Economy and Educational Reforms in the Global South: An Evolutionary Study of Ghana
• Electoral Militarization and the Challenges of Free and Fair Elections in Nigeria: A Focus on the 2023 Presidential Election
• Political Awareness and Engagement in Relation to Voting Behavior among College Students
• Role of Community Leaders in Ensuring Secure Electoral Process in Nairobi City County, Kenya
• Assessing the Delivery of Local Disaster Management Services and Client Satisfaction through SERVQUAL Dimensions