Impact of Artificial Intelligence on Cybersecurity in Nigeria

David Mark ()

American Journal of Computing and Engineering, 2024, vol. 7, issue 4, 1 - 11

Abstract: Purpose: The aim of the study was to assess the impact of artificial intelligence on cybersecurity in Nigeria. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The impact of artificial intelligence (AI) on cybersecurity has been profound, transforming how organizations detect, prevent, and respond to cyber threats. AI enhances threat detection capabilities by analyzing vast amounts of data to identify patterns and anomalies indicative of malicious activities, significantly reducing response times and improving accuracy. Machine learning algorithms continuously learn from new threats, enabling adaptive defenses that evolve with the threat landscape. Additionally, AI-driven automation streamlines routine security tasks, freeing up human analysts to focus on more complex issues. However, the adoption of AI in cybersecurity also introduces challenges, such as the potential for adversarial attacks where cybercriminals manipulate AI systems, and the ethical implications of increased surveillance and data privacy concerns. Implications to Theory, Practice and Policy: Complexity theory, sociotechnical systems theory and cognitive load theory may be used to anchor future studies on assessing the impact of artificial intelligence on cybersecurity in Nigeria. In the realm of practical application, industry-academia partnerships play a pivotal role. These partnerships should focus on developing and deploying AI-driven cybersecurity solutions tailored to diverse organizational contexts, challenges, and resource constraints. On the policy front, advocating for regulatory frameworks and standards is imperative.

Keywords: Artificial; Intelligence; Cybersecurity (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:bfy:ojajce:v:7:y:2024:i:4:p:1-11:id:2251

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