The Role of Machine Learning in Cyber-Security
DOI:
https://doi.org/10.64322/JLRP.2025.1105Keywords:
Machine Learning, Cyber-security, Cyber-attack, Challenges, Risk MitigationAbstract
The present defense system lacks combating force to deal with the cyber threats that have been getting more technically developed and creativity in committing of the crime. Machine learning (ML) technology, which is another aspect of artificial intelligence, has been a firm player in abetting the commission of crime. The best thing about machine learning is that it does not require much human surveillance and can analyze large databases and give solutions. Despite the odds of machine learning, this can also be useful in combating cyber-crime. This paper carefully looks at the different aspects of machine learning (ML) that can be used in providing cybersecurity. Machine learning can be used in detecting advanced threats, analyzing complex malware, viruses, anticipating cyberthreats and monitor human behaviour for forecasting or otherwise which is complex, naturally unpredictable and does not have any straight cut jacket formula. It also critically examines the challenges encountered by machine learning like biasness, vulnerability towards cyber-attack and ethical challenges. On perusing the recent case studies, it reveals how machine learning has changed the modern day cybersecurity dimensions. The paper emphasizes the need for collaborative, interdisciplinary initiatives to mitigate the risks linked to machine learning deployment and to ensure its responsible and ethical application.
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