Security and Privacy in IoT Ecosystems

Citation: Prasanth Kosaraju, Venu Madhav Nadella, "Security and Privacy in IoT Ecosystems", Universal Library of Engineering Technology, Special Issue.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The rapid expansion of Internet of Things (IoT) ecosystems across smart homes, healthcare, transportation, and industrial environments has intensified concerns surrounding device security, data confidentiality, and user privacy. The heterogeneous and resource-constrained nature of IoT devices makes them highly susceptible to attacks, including device compromise, man-in-the-middle intrusions, insecure firmware exploitation, and large-scale botnets such as Mirai (Antonakakis et al., 2017). Additionally, the continuous, often passive collection of sensitive user data raises substantial privacy risks, enabling unauthorized profiling, behavioral inference, and surveillance (Zhang & Xu, 2020). Existing security frameworks remain challenged by the lack of standardized protocols, weak authentication mechanisms, and insufficient encryption practices suitable for lightweight IoT environments (Abbas et al., 2021). Recent studies emphasize the need for multi-layered protection approaches incorporating secure boot, encrypted communication, adaptive intrusion detection, and privacy-preserving techniques such as differential privacy and federated learning (Sharma et al., 2022). This research paper examines current security and privacy vulnerabilities across IoT architectures, analyzes emerging threat trends, and explores robust mitigation strategies to strengthen the resilience, trustworthiness, and ethical deployment of IoT systems.

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https://doi.org/10.70315/uloap.ulete.2022.009