Enhancing Cybersecurity with AI: From Anomaly Detection to Threat Mitigation

Abstract

Artificial Intelligence (AI) is revolutionizing the field of cybersecurity by enabling advanced techniques for anomaly detection and proactive threat mitigation. Traditional security measures often fall short in addressing the sophistication and frequency of modern cyberattacks. AI addresses this gap by leveraging machine learning, deep learning, and data analytics to detect, prevent, and respond to threats in real time. This paper explores the transformative role of AI in cybersecurity, focusing on its applications in anomaly detection, behavioral analysis, and automated incident response. Using evidence from case studies and industry practices, the findings highlight AI’s ability to enhance detection accuracy, reduce response times, and mitigate risks effectively. Challenges, such as algorithmic bias, adversarial threats, and resource demands, are critically analyzed. The study concludes by recommending strategies to optimize AI integration, emphasizing ethical implementation and collaboration to ensure a secure digital ecosystem.