Enhancing Network Security in Cloud-Integrated IoT Devices
Madhur Kumar, Manan Dhingra, Mahima Bhati, Sunita Joshi · 2024
Rapid growth in the Internet of Things (IoT) in cloud-integrated environments has exposed all critical areas for security vulnerabilities, characterized by increasingly sophisticated cyber threats and complex attack surfaces. Current security frameworks demonstrate fundamental inadequacies in providing protection across heterogeneous technological ecosystems. The research addresses the needs discussed by developing an innovative three-tier security architecture with blockchain authentication, federated deep learning, and adaptive encryption protocols. There is an overall objective to enhance network security through a dynamic, scalable framework capable of mitigating contemporary and emerging cyber threats. Experimental validation across 1,500 IoT nodes exhibits impressive performance improvements: 94% fewer unauthorized access attempts, 89% threat detection accuracy, and 76% incident response latency reduction. Such improvements are achieved with minimal computational overhead of 12% due to the proposed architecture. This work is expected to make a significant contribution in the area of cybersecurity research and technological innovation toward a comprehensive blueprint for next-generation security solutions, providing a robust data-driven methodology in securing distributed IoT infrastructures.