Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Kavitha, Rose; Gour, Shivashish; Arvind, Tripti; Selvanathan, S. Title A name given to the resource A Privacy-Preserving Federated Learning Protocol for Secure Analytics of IoT Sensor Data Using Homomorphic Encryption Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes in Electrical Engineering;Volume;1529 LNEE;pp.169-174 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-95-5835-3_27" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-95-5835-3_27</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105039488954?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105039488954?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kavitha R., Department of Management Studies, New Horizon College of Engineering, Outer Ring Road, Marathahalli, Kadabeesanahalli, Bengaluru, 560103, India; Gour S., Department of Computer Science and Engineering - BCT, Jain (Deemed-to-be) University, 45th km, NH - 209, Jakkasandra Post, Kanakapura Taluk, Ramanagara District, Karnataka, Bengaluru, 562112, India; Arvind T., School of Business and Management, Christ University, Hosur Main Road, Karnataka, Bengaluru, 560029, India, VHNSN College, Tamil Nadu, Virudhunagar, 626001, India; Selvanathan S., VHNSN College, Tamil Nadu, Virudhunagar, 626001, India Description An account of the resource The proliferation of Internet of Things (IoT) devices has led to massive amounts of sensitive data generation, making data security a paramount concern. Existing methods often struggle with protecting heterogeneous IoT data efficiently, particularly during model training and communication. In this work, we propose a federated learning framework integrated with secure encryption mechanisms to safeguard IoT data during model training and aggregation. Each client device trains a local model using its own sensor data, encrypts the model parameters, and sends them to a server. The server aggregates the encrypted models and sends back the global model for decryption by the clients, ensuring data privacy throughout the process. The proposed framework reduces the unauthorized access risks and also the experimental results demonstrate that the model results in an accuracy of 92% during prediction tasks. The system's encryption overhead was minimal, with only a 7.5% increase in computation time compared to unencrypted federated learning methods. Future work will focus on optimizing the encryption techniques for resource-constrained IoT devices and exploring adaptive security mechanisms powered by machine learning to detect emerging threats dynamically. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Federated Learning; Homomorphic Encryption; Internet of Things (IoT); Secure IoT Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 18761100; ISBN: 978-981955834-6; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online