AI-Driven Cybersecurity Solutions: Case Studies and Applications
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Abstract
The increasing sophistication of cyberattacks in recent years has led to a growing reliance on artificial intelligence (AI) for advanced cybersecurity solutions. AI-driven cybersecurity systems offer unparalleled speed, adaptability, and precision in detecting, responding to, and mitigating threats. This research paper explores the application of AI in cybersecurity, focusing on real-world case studies and key technologies, such as machine learning, deep learning, and natural language processing. We examine the effectiveness of AI in areas such as threat detection, anomaly detection, and automated incident response, along with the challenges of integrating AI into cybersecurity infrastructures. Additionally, this paper discusses the limitations and potential risks associated with AI-driven security, such as adversarial attacks. The findings highlight how AI-based cybersecurity solutions are transforming the landscape of digital security, making it more proactive and adaptive in addressing evolving cyber threats, while also stressing the need for continuous innovation to counter adversarial actors.
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