A Secure and Scalable Cloud Data Framework Using Key-Aggregate Encryption and Optimization-Based Routing

Abstract Objectives: To design secure and scalable cloud frame work that integrates Key- Aggregate Encryption (KAC), routing and optimization techniques to enhance the data security, reduce computation and to increase the overall system performance. Method: A secure and scalable cloud data framework integrating Key-Aggregate Encryption (KAC), fuzzy trust-based routing, and Butter-Ant Optimization (BAO) was developed. Blowfish was applied with the SHA-3 hashing to guarantee a high level of data confidentiality and integrity. The choice of Blowfish is grounded on its low computation cost, increased encryption rate, and the aptness to resource-constrained IoT systems, and on the fact that SHA-3 is highly resistant to collision attacks and preimage attacks. These algorithms are contrasted to AES and Attribute-Based Encryption (ABE) regarding the time of encryption, complexity, and scalability. The framework was implemented in a Python-based simulation environment using healthcare IoT datasets. The performance of the proposed system was evaluated in terms of packet delivery ratio, end-to-end delay, routing overhead, and encryption time. Findings: The proposed framework was evaluated using a simulated healthcare IoT dataset consisting of physiological sensor data. The experimental findings show that the framework has a ratio of the packet being delivered of 96.8, an average end-to-end delay of 42.3 ms, a routing overhead of 11.6, an encryption time of 8.9 ms, and a decryption time of 9.4 ms. The improved framework has an advantage over traditional trust- and attribute-based encryption based routing and encryption schemes, in the sense that it has shown greater delivery efficiency, lesser delay and less computational overhead. Novelty: The novelty of the suggested model is the combination of Key-Aggregate Encryption and trust-aware routing and optimization methods in secure and scalable cloud-based systems of IoT. One such example is when using a healthcare cloud environment, patient data obtained by wearable IoT devices shall be relayed in optimized routes and stored in cloud servers, whereby doctors can access numerous patient records with a single aggregate key. This goes a long way in reducing critical management overheads and at the same time facilitating safe and effective data sharing. Keywords: Cloud Security, Key-Aggregate Encryption, Trust-Aware Routing, Optimization Algorithms, Secure Cloud Storage