Statistical Image Classification for Image Steganographic Techniques

Seyyedi, Seyyed Amin; Ivanov, Nick

doi:10.5815/ijigsp.2014.08.03

Cited by 12 publications

(5 citation statements)

References 17 publications

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“…In image classification, the crucial step is to analyze the properties of image features and to organize the numerical features into classes. In other words, an image is classed according to its contents [1,2,3,4,5,6].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Feature Extraction Methods in Images Classification

Medjahed¹

2015

IJIGSP

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Feature extraction is an important step in image classification. It allows to represent the content of images as perfectly as possible. However, in this paper, we present a comparison protocol of several feature extraction techniques under different classifiers. We evaluate the performance of feature extraction techniques in the context of image classification and we use both binary and multiclass classifications. The analyses of performance are conducted in term of: classification accuracy rate, recall, precision, f-measure and other evaluation measures. The aim of this research is to show the relevant feature extraction technique that improves the classification accuracy rate and provides the most implicit classification data. We analyze the models obtained by each feature extraction method under each classifier.

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Section: Introductionmentioning

confidence: 99%

A Comparative Study of Feature Extraction Methods in Images Classification

Medjahed¹

2015

IJIGSP

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“…The two categories of data hiding are digital watermarking and steganographic applications. Data hiding aims to hide secret information in cover media without detectable [20]. Cryptography and steganography technique to encrypt and hide data using one-time-pad technique and DNA sequences technique [21].…”

Section: Introductionmentioning

confidence: 99%

DNA-Genetic Encryption Technique

Mousa¹

2016

IJCNIS

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Abstract-In this paper, we propose DNA-Genetic Encryption Technique (D-GET) in order to make the technique more secure and less predictable. In this technique, binaries any type of digital data and convert it to DNA sequencing, reshape, encrypt, crossover, mutate and then reshape. The main stages of D-GET are repeated three times or more. Transmit the encrypted data in text/image format file. In other side, the receiver uses the D-GET to decrypt the received data and reshape it to original format. This Technique also transforms the text into an image and vice versa to improve security and multiple key sequences to increase the degree of diffusion and confusion, which makes resulting cipher data difficult to decipher and makes to realize a perfect secrecy system. Experimental results demonstrate that proposed technique has multilayer protection stages against different attacks and higher level of security based on the multi-stages and genetic operations. Decrypted data are acceptable because of there is absolutely difference between it and secret data.

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“…In Distortion Method, the cover media is distorted and a special technique is used to embed the secret message in such a way as to correct the distorted carrier (Medeni & Souidi, 2010;Gaikwad & Wagh, 2010); Statistical Method where the effort is to overcome the statistical analysis approaches to steganalysis using such properties as statistical features of the cover media file, which include mean, standard deviation, variance, histogram analysis, correlation coefficient, texture similarities, entropy, marginal distribution, second-order statistics, etc. (Sarkar, et al, 2007;Sadkhan, et al, 2009;Sun & Lui, 2010;Seyyedi & Ivanove, 2014); Transform Domain Methods, where the cover media signal such as the frequency domain is transformed using standard mathematical concepts such as Integer Wavelet Transform (IWT), Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Arnold Transform are often used (Haynes, 2011;; and Spatial-Domain Method, also called Substitution method is the commonly used steganography methods. They are simple to understand and implement; requiring fewer resources during embedding and retrieval of hidden secret messages.…”

Section: Introductionmentioning

confidence: 99%

A Novel Structured-Least Significant Bit Steganography Technique

Zachariah¹

2016

IJISE

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The need for improved security in data communications has been the driving force behind the several types of research that describes various techniques for implementing security policies and systems. The use of Steganography and Cryptography has made a high impact in advancing the security desired of data communications. However, there is a continuous need to more research that would deal with loopholes inherent in security systems. This research proposes a novel structured-least significant bit steganography technique which embeds secret messages in such a way that retrieval of such message is difficult for a third party, a hacker. The proposed technique was implemented and tested against most relevant existing techniques and was found to perform better in terms of the quality of the cover and Stego-image analysis.

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Statistical Image Classification for Image Steganographic Techniques

Cited by 12 publications

References 17 publications

A Comparative Study of Feature Extraction Methods in Images Classification

A Comparative Study of Feature Extraction Methods in Images Classification

DNA-Genetic Encryption Technique

A Novel Structured-Least Significant Bit Steganography Technique

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