Authors:
- Explores in detail an Artificial Intelligence-based socio-inspired optimization algorithm referred to as Cohort Intelligence (CI)
- Focuses on the steganography approach, along with Cognitive Computing (CC) and a Multi-Random Start Local Search (MRSLS) optimization algorithm
- Presents a range of optimization models used in steganography
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 187)
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Table of contents (8 chapters)
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Front Matter
About this book
This book explores the use of a socio-inspired optimization algorithm (the Cohort Intelligence algorithm), along with Cognitive Computing and a Multi-Random Start Local Search optimization algorithm. One of the most important types of media used for steganography is the JPEG image. Considering four important aspects of steganography techniques – picture quality, high data-hiding capacity, secret text security and computational time – the book provides extensive information on four novel image-based steganography approaches that employ JPEG compression. Academics, scientists and engineers engaged in research, development and application of steganography techniques, optimization and data analytics will find the book’s comprehensive coverage an invaluable resource.
Authors and Affiliations
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Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India
Dipti Kapoor Sarmah, Anand J. Kulkarni
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Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR), Auburn, USA
Ajith Abraham
Bibliographic Information
Book Title: Optimization Models in Steganography Using Metaheuristics
Authors: Dipti Kapoor Sarmah, Anand J. Kulkarni, Ajith Abraham
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-030-42044-4
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-42043-7Published: 26 February 2020
Softcover ISBN: 978-3-030-42046-8Published: 26 February 2021
eBook ISBN: 978-3-030-42044-4Published: 25 February 2020
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XIII, 166
Number of Illustrations: 64 b/w illustrations, 25 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Image Processing and Computer Vision