Fourier Finite Mellin Transform Based Data Hiding Methods for Data Security and Privacy in Cloud

Abstract

In recent years, cloud computing has seen significant growth due to its cost-effective and convenient services. Cloud data services have become a popular choice for storing enterprise data, as an increasing number of companies and users are migrating their data to the cloud. However, ensuring the privacy and security of this data remains a critical challenge that must be addressed to fully leverage cloud services. Data security plays a vital role in both the storage and transmission of cloud data. Using data hiding techniques can be an effective approach to enhance the security of data storage and transmission in the cloud. This paper presents a review of various data encryption methods, steganography techniques, and hybrid approaches that have been widely used in this field. However, many of these methods face challenges related to the overheads associated with encryption and the considerable computational time required. There is a growing need for a new approach that ensures cloud security without relying on encryption processes. Such an approach would reduce the burdens of encryption, leading to improved overall performance. At this point, data hiding methods emerge as a promising and effective alternative to encryption-based security measures for cloud data storage. In this paper, finite Mellin transform based hybrid encryption model is developed for securing the sensitive data.