Nowadays, national security issues are increasing day by day in most countries. A multitude of measures to reduce the challenges have been presented and even implemented by many authors, but without exhaustive results. The use of computers and sophisticated IT tools by the terrorist group, increasing number of citizens, lack of social amenities and other factors have made some of them inadequate enough to control the problems in Nigeria. The purpose of this paper is to highlight national security challenges in Nigeria and how security oversight is operated. To achieve this, the authors analyze available secondary data, investigating national security modus operandi and presenting the general concept of surveillance. Related works were also investigated for discussion. Remote surveillance, wiretapping, geospatial intelligence and a consolidated national database are proposed to achieve digital intelligence collection for insecurity management.
The research was conducted in the field of publishing data to preserve confidentiality. Several educational datasets have been used to address privacy and utility. The sample questionnaires served to investigate the level of privacy awareness and enforcement in the records of students in tertiary institutions in Kebbi State, Nigeria. The benchmark datasets were obtained from Kebbi State Polytechnic Dakin-gari. K-anonymity and l-diversity models were used with k configurations and suppression limits of 10 and 50% in the ARX 3.9.0 de-anonymization environment. The work evaluates data privacy, quality, and execution time for each k value and suppressions limit. Experimental results demonstrate that the higher the suppression the more balanced exists between privacy and utility. It was observed that suppression of 50% provides less anonymization time irrespective of k compared to k values in suppression = 10%. This was proved to be due to less time it takes anonymization to be completed Also, from respondents, 92% of students’ records were kept permanently in plain and, issued to third parties like that—with no privacy guarantee. This poses privacy threats to datasets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.