2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 16 , Issue 1 , PP: 85-100, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Abhishek Kumar 1 * , Samta Jain Goyal 2 , Sumit Kumar 3 , Hitesh Kumar Sharma 4
Doi: https://doi.org/10.54216/FPA.160107
IoT devices have transformed smart cities and healthcare. The expanding usage of IoT devices creates major security threats, leaving critical systems vulnerable to sophisticated and persistent assaults. Our hybrid IoT security approach employs homomorphic encryption and improved MobileNet to protect data and simplify feature extraction. Our extensive testing and assessment prove that the proposed structure makes IoT settings more resistant to sophisticated persistent attacks. We discovered superior methodologies for F1 score, accuracy, precision, and memory performance measurement. To ensure data privacy and security during analysis and transmission, homomorphic encryption is incorporated. Our ablation research lays out each framework component's contributions. To increase system speed, it emphasizes safe data processing, real-time analytical optimization, lightweight feature extraction, and privacy-preserving computing. The scalability study indicates that the framework can scale with IoT installations while maintaining peak performance and resource efficiency. Finally, the hybrid IoT security architecture improves IoT security. It provides a full and effective security solution for IoT infrastructure. Lawmakers, business experts, and students in the sector may learn from this research regarding genuine IoT security systems.
Advanced Persistent Threats , Data Privacy , Encryption , Feature Extraction , Homomorphic Encryption , Internet of Things , Lightweight , MobileNet , Security Frameworks , Threat Mitigation.
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