Optimization Models in Steganography Using Metaheuristics

This book offers an in-depth look at optimizing steganography techniques using innovative algorithms, including the Cohort Intelligence algorithm. Optimization Models in Steganography Using Metaheuristics serves as a vital resource for researchers and practitioners.

This book delves into innovative methodologies for optimizing steganographic techniques, particularly through the lens of a socio-inspired optimization algorithm known as the Cohort Intelligence algorithm. In conjunction with Cognitive Computing and a Multi-Random Start Local Search optimization algorithm, the text presents a thorough examination of these advanced strategies. The integration of these concepts aims to enhance the efficacy and reliability of steganography practices.

A significant focus of Optimization Models in Steganography Using Metaheuristics is the utilization of JPEG images, which serve as a vital medium for steganographic applications. The book thoroughly investigates four critical aspects of steganography techniques: picture quality, data-hiding capacity, secret text security, and computational time. By addressing these elements, the author provides insights into how novel image-based steganography approaches can leverage JPEG compression to achieve superior results.

Targeted towards academics, scientists, and engineers involved in the research and development of steganography techniques, this book offers a comprehensive resource. It is designed to support those engaged in optimization and data analytics, making it a valuable addition to the literature on steganography. Readers will find the extensive information and innovative approaches presented in Optimization Models in Steganography Using Metaheuristics to be both informative and practical for their work in the field.