Privacy-Preserving Deep Learning Framework For Secure Predictive Analytics In Industrial IIoT

Authors: Ms. Neha Yadav, Dr. Nitin Kumar

Abstract: The rapid adoption of the Industrial Internet of Things (IIoT) will continue to transform industrial operations by enabling real-time monitoring, intelligent automation, and data-driven decision-making. However, the increasing deployment of interconnected sensors, controllers, and smart devices will expose industrial systems to significant cyber security threats, data breaches, and privacy concerns. Conventional predictive analytics approaches will often fail to provide robust security while maintaining high prediction accuracy in dynamic industrial environments. Therefore, this study will propose a Secure Deep Learning Framework for Predictive Analytics in Industrial Internet of Things (IIoT) that will integrate advanced deep learning models with multi-layer security mechanisms to enhance both predictive performance and data protection.

DOI: http://doi.org/10.5281/zenodo.21641494