01226nas a2200157   4500000000100000008004100001260001500042100003000057700003200087700002400119700003100143245009100174856010800265520068100373022001401054       2024                            d  c2024-01-301 aUgochukwu Ikechukwu Okoli1 aTemitayo Oluwaseun Abrahams1 aOgugua Chimezie Obi1 aAdebunmi Okechukwu Adewusi00aMachine learning in cybersecurity: A review of threat detection and defense mechanisms  uhttps://wjarr.com/content/machine-learning-cybersecurity-review-threat-detection-and-defense-mechanisms3 aThis paper examines the significance of ML in the field of cybersecurity, with a special emphasis on the identification of threats and the implementation of protective measures. By incorporating ML algorithms into cybersecurity frameworks, organisations may automate decision-making processes, facilitating prompt responses to ever-changing threats. Lastly, the paper covers the obstacles and ethical issues related to the adoption of ML in cybersecurity. Issues like as adversarial assaults, skewed datasets, and the interpretability of ML models are examined, highlighting the necessity for a holistic strategy that integrates modern technology with ethical considerations.   a2581-9615