Secure Communication Protocols for Privacy and Data Protection in IoT-Enabled Devices
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Abstract
The rapid proliferation of Internet of Things (IoT) devices has revolutionized data collection, automation, and connectivity across various sectors, including healthcare, smart homes, industrial automation, and transportation. However, the widespread adoption of IoT introduces significant privacy and security challenges due to the heterogeneous nature of devices, constrained computational resources, and the exposure of sensitive data to potential cyber threats. Secure communication protocols play a pivotal role in safeguarding data privacy and integrity while ensuring reliable device-to-device and device-to-cloud interactions. This paper investigates state-of-the-art secure communication protocols tailored for IoT environments, focusing on their effectiveness in ensuring privacy, data protection, and resistance against cyber-attacks such as eavesdropping, man-inthe-middle, and replay attacks. The study evaluates protocols including Datagram Transport Layer Security (DTLS), Transport Layer Security (TLS), Lightweight Cryptography techniques, and blockchain-based communication frameworks, analyzing their suitability for resource-constrained IoT devices. A comparative performance analysis is conducted using simulation and real-world deployment scenarios, emphasizing security metrics, computational overhead, energy consumption, latency, and scalability. The research highlights the tradeoffs between robust security measures and the limited resources of IoT devices. Additionally, the paper explores privacypreserving mechanisms integrated into communication protocols, such as data anonymization and secure multi-party computation. Findings reveal that lightweight cryptographic protocols combined with adaptive security policies offer the best balance for IoT applications, while emerging blockchain-based solutions provide decentralized trust but face scalability challenges. The paper concludes with recommendations for protocol design considering IoT-specific constraints and evolving threat landscapes. Future research directions include the integration of Artificial Intelligence for anomaly detection within communication protocols and the development of standardized frameworks for secure IoT interoperability.
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References
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