Fangjun Huang

New Channel Selection Rule for JPEG Steganography

In this paper, we present a new channel selection rule for joint photographic experts group (JPEG) steganography, which can be utilized to find the discrete cosine transform (DCT) coefficients that may introduce minimal detectable distortion for data hiding. Three factors are considered in our proposed channel selection rule, i.e., the perturbation error (PE), the quantization step (QS), and the magnitude of quantized DCT coefficient to be modified (MQ). Experimental results demonstrate that higher security performance can be obtained in JPEG steganography via our new channel selection rule.

Attack LSB Matching Steganography by Counting Alteration Rate of the Number of Neighbourhood Gray Levels

In this paper, we propose a new method for attacking the LSB (least significant bit) matching based steganography. Different from the LSB substitution, the least two or more significant bit-planes of the cover image would be changed during the embedding in LSB matching steganography and thus the pairs of values do not exist in stego image. In our proposed method, we get an image by combining the least two significant bit-planes and divide it into 3x3 overlapped subimages. The subimages are grouped into four types, i.e. T 1,T 2, T 3 and T 4 according to the count of gray levels. Via embedding a random sequence by LSB matching and then computing the alteration rate of the number of elements in T 1, we find that normally the alteration rate is higher in cover image than in the corresponding stego image. This new finding is used as the discrimination rule in our method. Experimental results demonstrate that the proposed algorithm is efficient to detect the LSB matching stegonagraphy on uncompressed gray scale images.

Reversible Data Hiding in JPEG Images

Among various digital image formats used in daily life, the Joint Photographic Experts Group (JPEG) is the most popular. Therefore, reversible data hiding (RDH) in JPEG images is important and useful for many applications such as archive management and image authentication. However, RDH in JPEG images is considerably more difficult than that in uncompressed images because there is less information redundancy in JPEG images than that in uncompressed images, and any modification in the compressed domain may introduce more distortion in the host image. Furthermore, along with the embedding capacity and fidelity (visual quality), which have to be considered for uncompressed images, the storage size of the marked JPEG file should be considered. In this paper, based on the philosophy behind the JPEG encoder and the statistical properties of discrete cosine transform (DCT) coefficients, we present some basic insights into how to select quantized DCT coefficients for RDH. Then, a new histogram shifting-based RDH scheme for JPEG images is proposed, in which the zero coefficients remain unchanged and only coefficients with values 1 and -1 are expanded to carry message bits. Moreover, a block selection strategy based on the number of zero coefficients in each 8 × 8 block is proposed, which can be utilized to adaptively choose DCT coefficients for data hiding. Experimental results demonstrate that by using the proposed method we can easily realize high embedding capacity and good visual quality. The storage size of the host JPEG file can also be well preserved.

New Framework for Reversible Data Hiding in Encrypted Domain

In the past more than one decade, hundreds of reversible data hiding (RDH) algorithms have been reported. Via exploring the correlation between the neighboring pixels (or coefficients), extra information can be embedded into the host image reversibly. However, these RDH algorithms cannot be accomplished in encrypted domain directly, since the correlation between the neighboring pixels will disappear after encryption. In order to accomplish RDH in encrypted domain, specific RDH schemes have been designed according to the encryption algorithm utilized. In this paper, we propose a new simple yet effective framework for RDH in encrypted domain. In the proposed framework, the pixels in a plain image are first divided into sub-blocks with the size of

Distortion function designing for JPEG steganography with uncompressed side-image

m\times n

Improved Algorithm of Edge Adaptive Image Steganography Based on LSB Matching Revisited Algorithm

. Then, with an encryption key, a key stream (a stream of random or pseudorandom bits/bytes that are combined with a plaintext message to produce the encrypted message) is generated, and the pixels in the same sub-block are encrypted with the same key stream byte. After the stream encryption, the encrypted

Universal JPEG steganalysis based on microscopic and macroscopic calibration

m\times n

New JPEG steganographic scheme with high security performance

sub-blocks are randomly permutated with a permutation key. Since the correlation between the neighboring pixels in each sub-block can be well preserved in the encrypted domain, most of those previously proposed RDH schemes can be applied to the encrypted image directly. One of the main merits of the proposed framework is that the RDH scheme is independent of the image encryption algorithm. That is, the server manager (or channel administrator) does not need to design a new RDH scheme according to the encryption algorithm that has been conducted by the content owner; instead, he/she can accomplish the data hiding by applying the numerous RDH algorithms previously proposed to the encrypted domain directly.

Steganalysis of LSB Greedy Embedding Algorithm for JPEG Images using Coefficient Symmetry

In this paper, we present a new framework for designing distortion functions of joint photographic experts group (JPEG) steganography with uncompressed side-image. In our framework, the discrete cosine transform (DCT) coefficients, including all direct current (DC) coefficients and alternating current (AC) coefficients, are divided into two groups: first-priority group (FPG) and second-priority group (SPG). Different strategies are established to associate the distortion values to the coefficients in FPG and SPG, respectively. In this paper, three scenarios for dividing the coefficients into FPG and SPG are exemplified, which can be utilized to form a series of new distortion functions. Experimental results demonstrate that while applying these generated distortion functions to JPEG steganography, the intrinsic statistical characteristics of the carrier image will be preserved better than the prior-art, and consequently the security performance of the corresponding JPEG steganography can be improved significantly.

Feature Selection for High Dimensional Steganalysis

In edge adaptive image steganography based on LSB matching revisited algorithm (EAMR for short in this paper), the secret message bits are embedded into those consecutive pixel pairs whose absolute difference of grey values are larger than or equal to a threshold T. Tan et al. [1] pointed out that since those adjacent pixel pairs can be located by the potential attackers, the pulse distortion introduced in the histogram of absolute difference of pixel pairs (HADPP for short in this paper) can easily be discovered, and a targeted steganalyzer for revealing this pulse distortion is presented in [1]. In this paper, we propose an improved algorithm for EAMR, in which the adjacent pixel pairs for data hiding are selected in a new random way. Thus the attackers cannot locate the pixel pairs selected for data hiding accurately, and the abnormality that exists in HADPP cannot be discovered any longer. Experimental results demonstrate that our improved EAMR (I-EAMR) can efficiently defeat the targeted steganalyzer presented by Tan et al. [1]. Furthermore, it can still preserve the statistics of the carrier image well enough to resist today’s blind steganalyzers.