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Optimization Models in Steganography Using Metaheuristics: Intelligent Systems Reference Library, cartea 187

Autor Dipti Kapoor Sarmah, Anand J. Kulkarni, Ajith Abraham
en Limba Engleză Paperback – 26 feb 2021
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.

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Specificații

ISBN-13: 9783030420468
ISBN-10: 3030420469
Pagini: 166
Ilustrații: XIII, 166 p. 89 illus., 25 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.26 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Intelligent Systems Reference Library

Locul publicării:Cham, Switzerland

Cuprins

In MS

Textul de pe ultima copertă

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.


Caracteristici

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