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@article{204174,
        author = {Mr. Santosh Ajitrao Korde and Mrs. Vidya Sandeep Godbole},
        title = {SECURE DATA TRANSMISSION IN IOT DEVICES},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {1340-1345},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204174},
        abstract = {The rapid growth of the Internet of Things (IoT) has transformed various sectors, including healthcare, smart cities, industrial automation, agriculture, and transportation, by enabling seamless communication among interconnected devices. However, the widespread deployment of resource-constrained IoT devices has introduced significant security challenges, particularly in ensuring secure data transmission across heterogeneous networks. The transmission of sensitive information through wireless communication channels exposes IoT systems to various cyber threats such as eavesdropping, man-in-the-middle attacks, data tampering, replay attacks, and unauthorized access. Consequently, establishing robust security mechanisms for data transmission has become a critical requirement for maintaining confidentiality, integrity, authenticity, and availability of information within IoT ecosystems.
This study presents a comprehensive analysis of secure data transmission techniques in IoT devices, focusing on cryptographic algorithms, authentication protocols, key management schemes, and emerging security frameworks. The proposed approach integrates lightweight encryption mechanisms with mutual authentication protocols to address the limitations of computational power, memory, and energy consumption inherent in IoT devices. Advanced security technologies such as Elliptic Curve Cryptography (ECC), Advanced Encryption Standard (AES), Transport Layer Security (TLS), Datagram TLS (DTLS), blockchain-based security models, and machine learning-assisted intrusion detection systems are examined to enhance communication security. Furthermore, the research investigates the role of edge and fog computing in reducing latency while ensuring secure transmission and real-time threat detection. The proposed framework employs a multi-layer security architecture that combines device authentication, encrypted communication channels, secure key exchange, and continuous monitoring to mitigate potential vulnerabilities. Performance evaluation is conducted based on parameters such as encryption overhead, energy efficiency, transmission delay, throughput, and resistance to cyberattacks. Experimental findings indicate that lightweight cryptographic solutions coupled with intelligent threat detection mechanisms significantly improve transmission security while maintaining acceptable resource utilization. The results demonstrate enhanced protection against common IoT attacks without compromising network performance or scalability. This research contributes to the development of resilient IoT communication infrastructures by providing a scalable and efficient security framework for secure data transmission. The proposed methodology offers practical insights for researchers, developers, and industry practitioners seeking to implement secure and reliable IoT systems in increasingly connected environments. Future work may explore the integration of quantum-resistant cryptographic techniques and artificial intelligence-driven adaptive security mechanisms to address evolving cybersecurity threats in next-generation IoT networks.},
        keywords = {Internet of Things (IoT), Secure Data Transmission, Lightweight Cryptography, AES, ECC, Authentication, DTLS, Blockchain, Intrusion Detection System, Cybersecurity, Data Integrity, Confidentiality.},
        month = {June},
        }