Cloud Data Security using Balanced Genetic Algorithm

In computer science, data plays a vital role in accessing the core architecture of any product. Nowadays, cloud computing has emerged as a new paradigm to store data and services. It provides a computational architecture where users can send their data and performs any operation on it. with the growing demands of the cloud, it has become a major area of concern as it contains sensitive data. Data protection and maintaining the integrity of data are the key issues in the cloud due to its capability to store information at different geo-locations. The data security model of the cloud needs special attention as new threats and vulnerabilities are getting introduced day by day. The available standard encryption algorithms that provide data security, have their own limitations and must be addressed at any cost. We are proposing a methodology called the Balanced Genetic Algorithm (BGA) to address the underlined problem statement of data security in the cloud. The idea is to balance the existing genetic algorithm to provide scalability, enhance security, and decouple the data life cycle from the core encryption terminology. With our experimental result, we have shown that the proposed idea has better performance than the current standard encryption techniques.