Hafif şifreleme entegrasyonu Güvenlik için bir izleme ve değerlendirme çerçevesi IoT teknolojisiyle desteklenen verimli bir bulut tabanlı sistem

In the present generation, security issues are a major issue experienced by everyone due to the increase in digital technologies. With the introduction of digital technologies, data is stored and transmitted through platforms where security issues arise. Many cryptographic techniques are available to protect data in transmission and storage through digital technologies to overcome security issues. The methods are utilized to encrypt the data with passwords or PIN codes, which hackers can easily identify. In this case, for a safe process, a hybrid encryption method is proposed in this thesis for security data purposes, integrated with lightweight and hidden ciphertext policy attributes with the assistance of the cloud IoT environment. The lightweight encryption provides proxy services for data authentication. The analysis of the security has provided a positive impact on the encryption of the integrated lightweight. The system offers better positive results with hybrid encryption for data authentication for security purposes. The third part of the framework introduces a hybrid encryption system that combines a hidden hierarchical policy with a lightweight Ciphertext Policy Attribute-Based Encryption (CP-ABE) enforcement model. This is to ensure fine grained access control, minimal computational burden, and efficient encryption-decryption suited for IoT devices. It also incorporates QGE-HMAC for secure message authentication and ELP-DSA for signature validation, providing strong protection for encryption key integrity and end-to-end data authenticity. The final part presents a reliable cloud-enabled IoT network monitoring system powered by JPAO-GRU. This advanced gated recurrent unit model integrates Aranda-Ordaz activation and Jeffreys prior regularization for accurate anomaly detection. Additionally, the framework includes HTT-Fuzzy logic for outdated device detection, QASOA for intelligent load balancing, and LCA-BST for low-latency, Hierarchical device monitoring. Comprehensive experimental validation shows that the The proposed dual approach enhances security, integrity, and network efficiency, achieving high accuracy (99.12%) in intrusion detection, 99.18% encryption security, and substantial reductions in encryption time, latency, and energy consumption. This research contributes a A unified and scalable solution for addressing the growing security, authentication, and trust challenges in next-generation cloud-IoT systems.