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@article{183420,
        author = {Anoop Purushotaman},
        title = {Architecting Cyber Hygiene Metrics with Scalable Data Lakes},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {3},
        pages = {2325-2330},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=183420},
        abstract = {As threats in cyberspace become more in size and complexity, scalable data lakes have become a critical architecture for computing and auditing cyber hygiene metrics. This article combines the state-of-the-art in systems that include big data frameworks, AI-powered analytics, and governance constructs to drive forward-thinking cyber hygiene measurement. We examine performance assessment, scalability research, and AI-powered detection systems, and introduce a theoretical model to inform future implementations. Major challenges such as metric standardization, adaptive tuning, and compliance readiness are realized, and future research directions are established to facilitate robust, explainable, and automated cyber hygiene frameworks.},
        keywords = {Cyber hygiene, data lakes, cybersecurity metrics, scalable architecture, AI analytics, governance, future directions},
        month = {August},
        }