Enhancing Security in Cloud Computing Using Artificial Intelligence (AI) Techniques
DOI:
https://doi.org/10.47941/ijce.2764Keywords:
Machine Learning, Deep Learning, Natural Language Processing, Intrusion Detection Systems, Threat Intelligence, Cybersecurity.Abstract
Cloud computing has revolutionized data storage, processing, and accessibility, but it also introduces significant security challenges, including data breaches, insider threats, unauthorized access, and distributed denial-of-service (DDoS) attacks. Traditional security approaches, such as rule-based firewalls and static access control mechanisms, struggle to counter increasingly sophisticated cyber threats. Artificial Intelligence (AI) has emerged as a transformative solution, leveraging machine learning (ML), deep learning (DL), and natural language processing (NLP) to enhance cloud security. AI-driven threat detection systems analyze vast datasets in real time, identifying anomalies and predicting potential attacks with high accuracy. AI-powered automated incident response mechanisms help mitigate security risks by proactively addressing vulnerabilities and adapting to evolving threats. The integration of AI techniques into cloud security frameworks, highlighting applications such as intelligent intrusion detection, adaptive authentication, AI-enhanced encryption, and automated compliance monitoring. The advantages AI brings in reducing response time, improving threat intelligence, and optimizing resource allocation. AI’s application in cybersecurity also poses challenges, including adversarial AI attacks, data bias, and computational overhead. By leveraging AI, organizations can achieve a more resilient and proactive defense against emerging cyber threats in cloud environments.
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