AI-Powered Proactive Threat Detection in Cloud-Based Insurance Systems Anomaly Detection Models in Practice
Keywords:
Proactive threat detection, Cloud security, Insurance systems, Anomaly detection models, AI applications, Data integrityAbstract
The insurance industry's increasing use of cloud-based technology creates new difficulties in preserving security while managing enormous volumes of private information. The use of AI powered anomaly detection models for proactive threat identification in cloud-based insurance platforms is examined in this study.
References
Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection: A survey. ACM Computing Surveys, 41(3), 1-58. https://doi.org/10.1145/1541880.1541882
Hawkins, D. M. (1980). Identification of Outliers. Springer.
Gu, G., Perdisci, R., Zhang, J., & Lee, W. (2014). BotMiner: Clustering analysis of network traffic for protocol- and structure-independent botnet detection. Proceedings of USENIX Security Symposium.
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Published
2024-12-02
How to Cite
Radhakrishnan Arikrishna Perumal,. (2024). AI-Powered Proactive Threat Detection in Cloud-Based Insurance Systems Anomaly Detection Models in Practice . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2518–2531. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2162
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