An Effective Cloud Data Security Framework for Real-Time Cloud Computing Environments Based on Dynamic Keyword Search

Abstract

Most of the existing secure keyword search models are infeasible and not applicable for massive sets due to their high computational and memory requirements for data processing and dynamic security parameter initialization along with integrity size, which leads to an exponentially huge computational search space. It is more difficult to keep the data in the public/ private cloud server safe. Particularly, we are considering the unstructured data formats which are extremely hard to keep data structure and avoid error. It plans to develop and implement a hybrid dynamic keyword-based cloud data security framework for large cloud databases. This framework combines a hybrid dynamic hash-based keyword search and encryption and decryption model into a unique concept especially provided for the cloud environment based on a unique non-linear chaotic hash algorithm and a hybrid multi-user-based encryption and decryption model to accomplish a dynamic cloud data and service access and protection via a static keyword-based cloud data security framework for Big-Data structure and tasks.  Experimental results show that this model presents faster runtime for keyword search or decryption/encryption operation compared to conventional models. Therefore, the proposed model will pave the way for those data security experts working with the cloud data storage system.