Multi-Class Classification for Identifying JPEG Steganography Embedding Methods von Rodriguez, Benjamin M: New (2012)

Beschreibung

Print on Demand pp. 194.

Bestandsnummer des Verk�ufers 390046720

Verk�ufer kontaktieren

Diesen Artikel melden

Bibliografische Details

Titel: Multi-Class Classification for Identifying JPEG Steganography Embedding Methods
Verlag: Biblioscholar
Erscheinungsjahr: 2012
Sprache: Englisch
ISBN-10: 1288311931
ISBN-13: 9781288311934
Einband: Softcover
Zustand: New

�ber diesen Titel

Inhaltsangabe

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.

Rese�a del editor

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.

��ber diesen Titel� kann sich auf eine andere Ausgabe dieses Titels beziehen.