• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1938-1962
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• 2015

Security of information during transmission is a major issue in this modern era. All of the communicating bodies want confidentiality, integrity, and authenticity of their secret information. Researchers have presented various schemes to cope with these Internet security issues. In this context, both steganography and cryptography can be used effectively. However, major limitation in the existing steganographic methods is the low-quality output stego images, which consequently results in the lack of security. To cope with these issues, we present an efficient method for RGB images based on gray level modification (GLM) and multi-level encryption (MLE). The secret key and secret data is encrypted using MLE algorithm before mapping it to the grey-levels of the cover image. Then, a transposition function is applied on cover image prior to data hiding. The usage of transpose, secret key, MLE, and GLM adds four different levels of security to the proposed algorithm, making it very difficult for a malicious user to extract the original secret information. The proposed method is evaluated both quantitatively and qualitatively. The experimental results, compared with several state-of-the-art algorithms, show that the proposed algorithm not only enhances the quality of stego images but also provides multiple levels of security, which can significantly misguide image steganalysis and makes the attack on this algorithm more challenging.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.244-249
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• 2017

Steganalysis is to detect information hidden by steganography inside general data such as images. There are stegoanalysis techniques that use machine learning (ML). Existing ML approaches to steganalysis are based on extracting features from stego images and modeling them. Recently deep learning-based methodologies have shown significant improvements in detection accuracy. However, all the existing methods, including deep learning-based ones, have a critical limitation in that they can only detect stego images that are created by a specific steganography method. In this paper, we propose a generalized steganalysis method that can model multiple types of stego images using deep learning. Through various experiments, we confirm the effectiveness of our approach and envision directions for future research. In particular, we show that our method can detect each type of steganography with the same level of accuracy as that of a steganalysis method dedicated to that type of steganography, thereby demonstrating the general applicability of our approach to multiple types of stego images.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.148-153
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• 2007

This paper deals with implementing a steganography based multi-modal biometric system. For this purpose, we construct a multi-biometrics system based on the face and iris recognition. Here, the feature vector of iris pattern is hidden in the face image. The recognition system is designed by the fuzzy-based Linear Discriminant Analysis(LDA), which is an expanded approach of the LDA method combined by the theory of fuzzy sets. Furthermore, we present a watermarking method that can embed iris information into face images. Finally, we show the advantages of the proposed watermarking scheme by computing the ROC curves and make some comparisons recognition rates of watermarked face images with those of original ones. From various experiments, we found that our proposed scheme could be used for establishing efficient and secure multi-modal biometric systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.840-855
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• 2011

In the context of additive noise steganography model, we propose a method to detect least significant bit (LSB) matching steganography in grayscale images. Images are decomposed into detail sub-bands with local linear transform (LLT) masks which are sensitive to embedding. Novel normalized characteristic function features weighted by a bank of band-pass filters are extracted from the detail sub-bands. A suboptimal feature set is searched by using a threshold selection algorithm. Extensive experiments are performed on four diverse uncompressed image databases. In comparison with other well-known feature sets, the proposed feature set performs the best under most circumstances.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.1
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• pp.69-75
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• 2014

Audio seganography is the art and science of writing hidden messages that evolves as a new secret communication method. And audio steganography is similar to the process of modifying the Least Significant Bit of image files 8th LSB layer embedding has been done for desired binary messages. The effective of steganographic tools is to obtain imperceptible and robust way to conceal high rate of secret data. The objective of this paper is to propose a method for hiding the secret messages in safer manner from external attacks by modified LSB technique and encryption rearrangement key.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2258-2274
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• 2020

In this paper we first propose a new cryptosystem based on our data hiding scheme (2,9,8) introduced in 2019 with high security, where encrypting and hiding are done at once, the ciphertext does not depend on the input image size as existing hybrid techniques of cryptography and steganography. We then exploit our automata approach presented in 2019 to design two algorithms for exact and approximate pattern matching on secret data encrypted by our cryptosystem. Theoretical analyses remark that these algorithms both have O(n) time complexity in the worst case, where for the approximate algorithm, we assume that it uses ⌈(1-ε)m)⌉ processors, where ε, m and n are the error of our string similarity measure and lengths of the pattern and secret data, respectively. In searchable encryption, our cryptosystem is used by users and our pattern matching algorithms are performed by cloud providers.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.5
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• pp.37-42
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• 2012

Audio steganography is quite similar to the procedure of modifying the least significant bit(LSB) of image media files. The most widely used technique today is hiding of secret messages into a digitized audio signal. In this paper, I propose a new method for hiding messages from attackers, high data inserting rate is achieved. In other words, based on the LSB hiding method and digitized to change the bit position of a secret message, an encrypted stego medium sent to the destination in safe way.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.71-76
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• 2007

This paper deals with implementing a steganography based multi-modal biometric system. For this purpose, we construct a multi-biometrics system based on the face and iris recognition. Here, the feature vector of iris pattern is hidden in the face image. The recognition system is designed by the fuzzy-based Linear Discriminant Analysis(LDA), which is an expanded approach of the LDA method combined by the theory of fuzzy sets. Furthermore, we present a watermarking method that can embed iris information into face images. Finally, we show the advantages of the proposed watermarking scheme by computing the ROC curves and make some comparisons recognition rates of watermarked face images with those of original ones. From various experiments, we found that our proposed scheme could be used for establishing efficient and secure multi-modal biometric systems.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.261-270
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• 2019

In order to protect secret digital documents against vulnerabilities while communicating, steganography algorithms are applied. It protects a digital file from unauthorized access by hiding the entire content. Pixel-value-difference being a method from spatial domain steganography utilizes the difference gap between neighbor pixels to fulfill the same. The proposed approach is a block-wise embedding process where blocks of variable size are chosen from the cover image, therefore, a stream of secret digital contents is hidden. Least significant bit (LSB) substitution method is applied as an adaptive mechanism and optimal pixel adjustment process (OPAP) is used to minimize the error rate. The proposed application succeeds to maintain good hiding capacity and better signal-to-noise ratio when compared against other existing methods. Any means of digital communication specially e-Governance applications could be highly benefited from this approach.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.395-402
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• 2004

In this paper, we proposed a new method of the large capacity steganography using adaptive threshold on bit planes. Applying fixing threshold, if we insert information into all bit planes, all bit planes showed different image quality. Therefore, we first defined the bit plane weight to solve the fixing threshold problem. We then proposed a new adaptive threshold method using the bit plane weight and the average complexity to increase insertion capacity adaptively. In the experiment, we inserted information into the standard images with the same image quality and same insertion capacity, and we analyzed the insertion capacity and image duality. As a result, the proposed method increased the insertion capacity of about 6% and improved the image quality of about 24dB than fixed threshold method.