Simplified Anti-Forensics of JPEG Compression

International Journal of Computer Applications, 2012

The influence of digital images on modern society is incredible, image processing has now become a significant component in almost all the areas. But storing images in a safe and sound way has become very complicated. Sometimes, for processing we can only use raster bitmap format. Therefore processing of such images should be carried out without knowledge of past processing on that image. Even though many image tampering detection techniques are available, the number of image forgeries is increasing. Therefore it is important to find the weaknesses of offered detection methods to prevent further forgeries. In this paper, a new approach is designed to prevent the bitmap compression history. Then it also explains how this can be used to perform unnoticeable forgeries on the bitmap images. It can be done by the estimation, examination and alteration in the transform coefficients of image. The existing methods for identification of bitmap compression history are JPEG detection and Quantizer estimation. The JPEG detection is used to find whether the image has been previously compressed. But the proposed method indicates that proper addition of noise to an image's transform coefficients can adequately eliminate quantization artifacts which act as indicators of JPEG compression. Using the proposed technique the modified image will appear to have never been compressed. Therefore this technique can be used to cover the history of operations performed on the image in the past and there by rendering several forms of image tampering.

Multimedia Research, 2020

In the past few years, the extensive appropriate of the JPEG image in transfer, storage, etc are rising. In the image, to recognize the local tampering the lossy character of the JPEG compression leaves of traces that are done using forensic agents. Here, by the JPEG compression, a difficult anti-forensic approach is developed to get rid of the traces left in both the spatial domain and DCT. A new improved sine-cosine (ISC) technique is developed on presented compression of anti-forensic format to optimally evaluate the noise-like signal to be augmented in the de-calibration and de-blocking operation. Additionally, in the optimization algorithm, a novel fitness function named Histogram Deviation (HD) is devised to appropriately balance the quality of visual and the undetectability of forensic. The simulation of the proposed anti-forensic compression method is done from the UCID database with the uncompressed images. The evaluation of the proposed technique is analyzed with the conventional techniques exploiting MSE, PSNR, and accuracy of classification as metrics. The simulation results show potential consequences such as high accuracy and low MSE that demonstrate the effectiveness of the proposed technique is deceptive the forensic agents.

Signal Processing: Image Communication, 2020

Identification of JPEG compressed images saved in uncompressed format (JPEG-U images) is an important issue in forensic analysis. The state-of-the-art JPEG compression detection methods fail to identify such images when subjected to post-processing/anti-forensic operations. In this paper, we propose a novel JPEG compression detector which is robust to post-processing and anti-forensic operations. The detector is based on the difference in the discrete cosine transform (DCT) coefficient distributions in the ac subbands of uncompressed images and JPEG-U images. We show theoretically and empirically that the probability of subband DCT coefficients which lie in the interval (−0.5, 0.5) is significantly different for a JPEG-U and the corresponding uncompressed image. This difference is exploited to derive a detection statistic which is compared with a threshold to detect JPEG-U images. The detector makes use of calibration, a technique used in steganalysis, to obtain the detection statistic. The experimental results show that the proposed detector significantly outperforms the state-of-the-art detectors, especially in the presence of post-processing and anti-forensic operations.

Forensic method which determine the forgery in the image. Similarly, Anti-forensic technique which makes fool of the forensics detectors and hides the trace of the operation done in the image. Now, we are proposing the anti-forensic method by using four steps. The first step normalize the image coefficients using total variation in the deblocking artifacts. The second work which uses dithering model for smoothening the image. The third work which again carries the first one with difference in the parameters and the final step is the balancing of the calibrated value in the image. By experimental simulation proves that the proposed work is efficient in terms of untraceability and image peculiarity than the existing system.

2012

Many forensic techniques recently tried to detect the tampering and manipulation of JPEG compressed images that became a critical problem in image authentication and origin tracking. Some techniques indicated that a knowledgeable attacker can make it very hard to trace the image origin, while others indicated that portions of the compressed image that has been compressed at different quality factor quantization matrices are distinguishable if they are recompressed at a higher quality factor quantization matrix (with less quantization steps). In this paper, we pursue the idea of recompressing forensically suspect-able images with different compression parameters. We use different quantization matrix sizes that would indicate a DCT projection at different frequencies (horizontally, vertically, and diagonally), and would make it easier to track any tampering or hacking footprints. We show that a JPEG compressed image can make these footprints distinguishable if recompressed with a smal...

Multimedia Tools and Applications, 2016

This paper presents a novel technique to discover double JPEG compression traces. Existing detectors only operate in a scenario that the image under investigation is explicitly available in JPEG format. Consequently, if quantization information of JPEG files is unknown, their performance dramatically degrades. Our method addresses both forensic scenarios which results in a fresh perceptual detection pipeline. We suggest a dimensionality reduction algorithm to visualize behaviors of a big database including various single and double compressed images. Based on intuitions of visualization, three bottom-up, top-down and combined top-down/bottom-up learning strategies are proposed. Our tool discriminates single compressed images from double counterparts, estimates the first quantization in double compression, and localizes tampered regions in a forgery examination. Extensive experiments on three databases demonstrate results are robust among different quality levels.

Nowadays with advancement of technology, tampering of digital images using computer and advanced software packages like Photoshop has become a simple task. Many algorithms have been proposed to detect tampered images that have been kept developing. In this regard, verification of accuracy of image content and detection of manipulations in image regardless of any previous knowledge about the image content and can be an important research field. Recently, many efforts have been made in the area of image forensics, especially passive algorithms for detecting tampered images. JPEG format is one of the most common formats used for image compression. Hence, JPEG images are subjected to attacks such as manipulation and cropping. Since single compressed and double compressed JPEG images contain blocking artifacts, therefore these images can be detected by assessment of these artifacts. JPEG artifacts will be not aligned in double compressed images which have been manipulated. This paper intends to examine challenges existing in blocking artifact extraction and improve the detection of double compressed JPEG images. Results of experiments show that new proposed approach has a proper functionality.

IOSR Journal of Computer Engineering, 2012

Medical imaging is the technique and process used to create images of the human body for clinical purposes or medical science.Image processing has now become a significant component in almost all the areas. But storing medical images in a safe and sound way has become very complicated. Processing of such images should be carried out without knowledge of past processing on that image. Even though many image tampering detection techniques are available, the number of image forgeries is increasing. In this paper, a new approach is designed to prevent the medical image compression history. Then it also explains how this can be used to perform unnoticeable forgeries on the medical images. It can be done by the estimation, examination and alteration in the transform coefficients of image. The existing methods for identification of compression history are JPEG detection and Quantizer estimation. The JPEG detection is used to find whether the image has been previously compressed. But the proposed method indicates that proper addition of noise to an image's transform coefficients can adequately eliminate quantization artifacts which act as indicators of JPEG compression. Using the proposed technique the modified image will appear to have never been compressed. Therefore this technique can be used to cover the history of operations performed on the image and there by rendering several forms of image tampering.

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA), 2016

This paper proposes an improved histogram-based approach to identifying whether an image is never compressed or has undergone JPEG compression with quality factor 100. The key idea is that the image's DCT (Discrete Cosine Transform) coefficients follow either of two families of parametric distributions, corresponding respectively to never compressed images and JPEG-100 compressed ones. This paper highlights that choosing the generalized Gaussian distribution (GGD) to model the DCT coefficients and constructing a DCT histogram with precision higher than integer create a prominent distinction between the DCT coefficients distribution of the two kinds of images. Experiments demonstrate that the proposed approach significantly outperforms existing histogram-based methods for the task of JPEG-100 forensics.

2006

The steady improvement in image/video editing techniques has enabled people to synthesize realistic images/videos conveniently. Some legal issues may occur when a doctored image cannot be distinguished from a real one by visual examination. Realizing that it might be impossible to develop a method that is universal for all kinds of images and JPEG is the most frequently used image format, we propose an approach that can detect doctored JPEG images and further locate the doctored parts, by examining the double quantization effect hidden among the DCT coefficients. Up to date, this approach is the only one that can locate the doctored part automatically. And it has several other advantages: the ability to detect images doctored by different kinds of synthesizing methods (such as alpha matting and inpainting, besides simple image cut/paste), the ability to work without fully decompressing the JPEG images, and the fast speed. Experiments show that our method is effective for JPEG images, especially when the compression quality is high.