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 Book Chapter Faculty Publications- Book Chapter 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 Dash, Adarsh Kumar; Sehgal, Chiranjeev; Dey, Hemangshu; Ramadani, Lauresha; Rajesh Kanna, R. Title A name given to the resource Modern privacy preserving strategies for IoT security Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived IoT Security: Fundamentals and Key Enabling Technologies;pp.125-136 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/B978-0-443-34125-0.00003-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/B978-0-443-34125-0.00003-9</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105026966910?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105026966910?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 Dash A.K., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India; Sehgal C., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India; Dey H., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India; Ramadani L., Computer Science Faculty, AAB College Prishtina, Kosovo, Prishtina; Rajesh Kanna R., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India Description An account of the resource The proliferation of Internet of Things (IoT) devices has brought about a revolution in various industries and everyday life, enhancing connectivity and efficiency. Nevertheless, this rapid adoption has also given rise to notable security and privacy challenges, leading to the need for robust solutions to safeguard sensitive data. This study delves into contemporary strategies for preserving privacy specifically designed for IoT security, with a focus on the most recent trends and technologies. By the year 2024, it is projected that the global count of IoT devices will exceed 30 billion, exhibiting a compound annual growth rate (CAGR) of 26.7% from 2021 to 2024. This exponential growth has led to a significant increase in the amount of data produced and transmitted by IoT devices, thereby creating fresh opportunities as well as vulnerabilities. Privacy apprehensions are crucial, given that these devices frequently amass sensitive personal and organizational data. The research scrutinizes cutting-edge privacy-preserving techniques, such as federated learning, homomorphic encryption, and differential privacy, which present promising resolutions for safeguarding data while upholding functionality. Federated learning has garnered attention as a decentralized approach that permits data processing to occur locally on devices rather than being sent to central servers, thereby reducing data exposure. Homomorphic encryption facilitates data processing while encrypted, ensuring a high level of security without disclosing the underlying information. Conversely, differential privacy introduces statistical noise to data, guaranteeing that individual data points are not easily discernible, thus preserving user privacy. This section also accentuates the significance of adhering to regulations and the impact of frameworks like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) on shaping the advancement and acceptance of privacy-preserving technologies. Moreover, an exploration is made into the incorporation of blockchain for immutable and transparent data management in IoT environments. This manuscript furnishes an exhaustive overview of the prevalent trends and technologies within this realm, providing insights into the future trajectory of IoT security and privacy. 2026 Elsevier Inc. All rights reserved.. Subject The topic of the resource Computer security; Computer security and privacy; Cryptography; Information systems; Network (computer science); Operations management Publisher An entity responsible for making the resource available Elsevier Relation A related resource ISBN: 978-044334125-0; 978-044334126-7; Language A language of the resource English Type The nature or genre of the resource Book chapter 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