Name: Multi-Class Classification for Identifying JPEG Steganography Embedding Methods (en Inglés)
Price: 227.04 PEN
Availability: InStock
Author: Rodriguez, Benjamin M.
ISBN: 9781288311934

portada Multi-Class Classification for Identifying JPEG Steganography Embedding Methods (en Inglés)

Formato

Libro Físico

Autor

Benjamin M. Rodriguez

Editorial

Biblioscholar

Idioma

Inglés

N° páginas

194

Encuadernación

Tapa Blanda

Dimensiones

24.6 x 18.9 x 1.0 cm

Peso

0.35 kg.

ISBN13

9781288311934

Categorías

Educación

Multi-Class Classification for Identifying JPEG Steganography Embedding Methods (en Inglés)

Benjamin M. Rodriguez (Autor) · Biblioscholar · Tapa Blanda

Libro Físico

S/ 227,04

S/ 454,07

Ahorras: S/ 227,04

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Envío normal

Origen: Reino Unido (Costos de importación incluídos en el precio)

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Reseña del libro "Multi-Class Classification for Identifying JPEG Steganography Embedding Methods (en Inglés)"

Over 725 steganography tools are available over the Internet, each providing a method for covert transmission of secret messages. This research presents four steganalysis advancements that result in an algorithm that identifies the steganalysis tool used to embed a secret message in a JPEG image file. The algorithm includes feature generation, feature preprocessing, multi-class classification and classifier fusion. The first contribution is a new feature generation method which is based on the decomposition of discrete cosine transform (DCT) coefficients used in the JPEG image encoder. The generated features are better suited to identifying discrepancies in each area of the decomposed DCT coefficients. Second, the classification accuracy is further improved with the development of a feature ranking technique in the preprocessing stage for the kernel Fisher's discriminant (KFD) and support vector machines (SVM) classifiers in the kernel space during the training process. Third, for the KFD and SVM two-class classifiers a classification tree is designed from the kernel space to provide a multi-class classification solution for both methods. Fourth, by analyzing a set of classifiers, signature detectors, and multi-class classification methods a classifier fusion system is developed to increase the detection accuracy of identifying the embedding method used in generating the steganography images.