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@article{182608,
        author = {Puranjay Das and Basavdutta Kar},
        title = {AI-Powered Threat Detection in Cloud Environments Strengthening Access Control Mechanisms},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {2647-2651},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182608},
        abstract = {The rapid emergence and evolution of cloud computing have revolutionized the way data is stored and processed. But it has also created various security issues that need to be resolved. Traditional access control methods are often unable to identify and prevent sophisticated threats.
This article explores the use of AI in enhancing the detection of threats and improving the security of cloud computing. Through the use of machine learning and behavioral analysis, AI-powered systems can provide more effective and efficient responses to prevent unauthorized access. This paper explores the various AI techniques that are used in the security of cloud computing. It also looks into their effectiveness in hybrid and multi-tenant cloud environments. The study states that threat detection through AI can help improve the agility and precision of access control and contribute to the resilience of modern cloud ecosystems.},
        keywords = {Artificial Intelligence (AI), Cloud Security, Threat Detection, Access Control, Machine Learning, Anomaly Detection, Behavioural Analytics, Cloud Computing, Insider Threats, Zero Trust Architecture, Multi-Tenant Cloud, Real-Time Monitoring, Data Privacy, Cybersecurity, Security Automation, Identity and Access Management (IAM), Cloud Infrastructure, Predictive Security, Adaptive Access Control, Intelligent Security Systems},
        month = {July},
        }