Image data hiding schemes based on metaheuristic optimization: a review

Abstract

The digital content exchange on the Internet is associated with information security risks. Hiding data in digital images is a promising direction in data protection and is an alternative to cryptographic methods. Steganography algorithms create covert communication channels and protect the confidentiality of messages embedded in cover images. Watermarking algorithms embed invisible marks in images for further image authentication and proof of the authorship. The main difficulty in the development of data hiding schemes is to achieve a balance between indicators of embedding quality, including imperceptibility, capacity, and robustness. An effective approach to solving this problem is the use of metaheuristic optimization algorithms, such as genetic algorithm, particle swarm optimization, artificial bee colony, and others. In this paper, we present an overview of data hiding techniques based on metaheuristic optimization. We review and analyze image steganography and image watermarking schemes over the past 6 years. We propose three levels of research classification: embedding purpose level, optimization purpose level, and level of metaheuristics. The results demonstrate the high relevance of using metaheuristic optimization in the development of new data hiding algorithms. Based on the results of the review, we formulate the main problems of this scientific field and suggest promising areas for further research.