AI and Machine Learning in Cybersecurity: Applications, Challenges and Future Directions
DOI:
https://doi.org/10.32628/CSEIT2612117Keywords:
Artificial Intelligence, Machine Learning, Cybersecurity, Threat Detection, Adversarial AI, Explainable AI, Intrusion Detection, Malware AnalysisAbstract
The types of cyber threats are becoming more and more complicated, so the classical security method which rely on signature is less applicable. Artificial Intelligence (AI) and Machine Learning (ML) are a few of technology giant for the world of cybersecurity, allowing the formulation of an effective plan to proactively fight these threats. The aim of this paper is to offer a comprehensive summary on AI/ML in cybersecurity. In this paper, we will examine the current AI/ML technology applied to cybersecurity. This is paper address a few of the dominant challenges in AI/ML, such as adversarial threats, data privacy .1 Introduction The rapid growth and increasing complexity of computing systems have led to significant advances and adaptation in artificial intelligence (AI) and machine learning (M L). This study also attempts to synthesize the current trends in the field by conducting a thorough survey of the literature review. Finally, the future directions in the field include Explainability, AI for security adaptation, and the need for integration with AI. This study highpoint AI/ML is not the silver bullet for the field of cybersecurity, it is imperative that strategic use of AI/ML is made in the design of next-generation cybersecurity systems.
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