Learning and Enhancing Cybersecurity Measures in Modern Technologies

Abstract:

Since cyber-attacks have become more advanced with new technology, cyber security is a significant concern in our evolving digital environment. The paper reviews how AI with machine learning (ML), deep learning (DL), and generative AI have helped improve cybersecurity from 2022 to 2025. These approaches prove to be very accurate, spotting threats with 94% precision and ridding systems of 97% of the malware types, but they can still cause unfairness, threaten privacy, and sometimes be applied in wrongful ways. In Nigeria, the slow development of infrastructure and changes in the law keep businesses from using AI. 21 backed studies reviewed and organized by researchers show that AI is useful for spotting dangers, conducting automatic actions, and looking ahead to new possibilities. Even so, the review finds that this technology falls short when it comes to being fair, transparent, and accessible to all regions. It was found that almost half of AI models are biased because the data they use is not representative. Only two out of five organizations in Nigeria have measures to keep sensitive data hidden. It suggests solutions built around ethics, better privacy, fair access, and cooperation among specialists to direct improvements in cybersecurity measures.

Keywords: Artificial intelligence (AI); Cybersecurity; Threat Detection; Ethical Implications; Predictive Analytics