Improved Cohort Intelligence—A high capacity, swift and secure approach on JPEG image steganography

Abstract

In the recent high level of information security was attained by combining the concepts of cryptography, steganography along with the nature inspired optimization algorithms. However, in today's world computational speed plays a vital role for the success of any scientific method. The optimization algorithms, such as cohort Intelligence with Cognitive Computing (CICC) and Modified-Multi Random Start Local Search (M-MRSLS) were already implemented and applied for JPEG image steganography for 8 × 8 as well as 16 × 16 quantization table, respectively. Although results were satisfactory in terms of image quality and capacity, the computational time was high for most of the test images. To overcome this challenge, the paper proposes modified version of cohort intelligence (CI) algorithm referred to as Improved Cohort Intelligence (CI). The Improved CI algorithm was considered as a cryptography technique and implemented to generate optimized cipher text. Improved CI algorithm was further employed for JPEG image steganography to propose a reversible data hiding scheme. Experimentation was done on grey scale image, of size 256 × 256; both for 8 × 8 and 16 × 16 quantization table. Results validation of the proposed work exhibited very encouraging improvements in the computational cost.