AI Driven Cybersecurity
DOI:
https://doi.org/10.62802/jg7gge06Keywords:
Artificial Intelligence, Cybersecurity, Machine Learning, Threat Detection, Predictive Analytics, Ethical AI, Resilient Systems, Anomaly DetectionAbstract
The advent of Artificial Intelligence (AI) has revolutionized the field of cybersecurity by introducing advanced mechanisms for detecting, preventing, and mitigating cyber threats. This research explores the intersection of AI and cybersecurity, highlighting the transformative potential of AI-driven solutions in combating increasingly sophisticated cyberattacks. By leveraging machine learning, deep learning, and neural network algorithms, AI enhances real-time threat detection, predictive analytics, and anomaly detection across diverse digital infrastructures. This study evaluates current AI-driven cybersecurity frameworks, emphasizing their efficacy in handling dynamic threat landscapes and addressing the limitations of traditional methods. Additionally, it examines ethical considerations, such as the potential misuse of AI by malicious actors and the need for transparent AI systems. Through comprehensive analysis, this research underscores the importance of developing resilient AI models to secure critical data and infrastructure in an era of rapidly evolving cyber risks. The findings provide actionable insights for policymakers, organizations, and technology developers, advocating for collaborative efforts to harness AI’s potential while addressing its inherent challenges.
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