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@article{184446,
        author = {Dr V Subrahmanyam and Dr M. V. Siva Prasad},
        title = {An Innovative Deep XAI Fusion Network for Interpretable Big Data Analytics and Secure Cloud Decision-Making Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {1469-1473},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184446},
        abstract = {The increasing reliance on big data analytics and intelligent cloud systems has enabled real-time decision-making across multiple domains such as healthcare, finance, and cybersecurity. However, the lack of transparency in deep learning models and the vulnerability of cloud-based infrastructures pose critical challenges. This research proposes an Innovative Deep XAI Fusion Network (DXFN) that integrates deep learning, explainable artificial intelligence (XAI), and secure cloud frameworks for interpretable and privacy-preserving decision- making. The proposed network fuses multi-layer attention-based interpretable deep models with federated cloud security protocols. Experimental simulations on healthcare and IoT -driven datasets demonstrate improved explainable (23% gain in SHAP interpretability score), accuracy (7–12% improvement over baseline CNN-LSTM models), and cloud data security compliance (AES-256 with block chain auditing). The results highlight the potential of DXFN in enabling trustworthy AI for critical decision-making in secure cloud environments.},
        keywords = {Deep Learning, Explainable Artificial Intelligence (XAI), Big Data Analytics, Secure Cloud Computing, Interpretable Decision-Making, Fusion Network.},
        month = {September},
        }