• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.75-81
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• 2014

In a distribution of the digital image, there is a serious problem that is distributed an illegal forgery image by pirates. For the problem solution, this paper proposes an image forensic decision algorithm using an edge energy information of forgery image. The algorithm uses SA (Streaking Artifacts) and SPAM (Subtractive Pixel Adjacency Matrix) to extract the edge energy informations of original image according to JPEG compression rate(QF=90, 70, 50 and 30) and the query image. And then it decides the forge whether or not by comparing the edge informations between the original and query image each other. According to each threshold in TCJCR (Threshold by Combination of JPEG Compression Ratios), the matching of the edge informations of original and query image is excused. Through the matching experiments, TP (True Positive) and FN (False Negative) is 87.2% and 13.8% respectively. Thus, the minimum average decision error is 0.1349. Also, it is confirmed that the performed class evaluation of the proposed algorithm is 'Excellent(A)' because of the AUROC (Area Under Receiver Operating Characteristic) curve is 0.9388 by sensitivity and 1-specificity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4005-4025
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• 2019

Copy-move forgery (CMF) in digital images is a detrimental tampering of artefacts that requires precise detection and analysis. CMF is performed by copying and pasting a part of an image into other portions of it. Despite several efforts to detect CMF, accurate identification of noise, blur and rotated region-mediated forged image areas is still difficult. A novel algorithm is developed on the basis of quaternion polar complex exponential transform (QPCET) to detect CMF and is conducted involving a few steps. Firstly, the suspicious image is divided into overlapping blocks. Secondly, invariant features for each block are extracted using QPCET. Thirdly, the duplicated image blocks are determined using k-dimensional tree (kd-tree) block matching. Lastly, a new technique is introduced to reduce the flat region-mediated false matches. Experiments are performed on numerous images selected from the CoMoFoD database. MATLAB 2017b is used to employ the proposed method. Metrics such as correct and false detection ratios are utilised to evaluate the performance of the proposed CMF detection method. Experimental results demonstrate the precise and efficient CMF detection capacity of the proposed approach even under image distortion including rotation, scaling, additive noise, blurring, brightness, colour reduction and JPEG compression. Furthermore, our method can solve the false match problem and outperform existing ones in terms of precision and false positive rate. The proposed approach may serve as a basis for accurate digital image forensic investigations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4567-4587
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• 2017

With the growth of the Internet and the extensive applications of image editing software, it has become easier to manipulate digital images without leaving obvious traces. Copy-move is one of the most common techniques for image forgery. Image blind forensics is an effective technique for detecting tampered images. This paper proposes an improved copy-move forgery detection method based on the discrete cosine transform (DCT). The quantized DCT coefficients, which are feature representations of image blocks, are truncated using a truncation factor to reduce the feature dimensions. A method for judging whether two image blocks are similar is proposed to improve the accuracy of similarity judgments. The main transfer vectors whose frequencies exceed a threshold are found to locate the copied and pasted regions in forged images. Several experiments are conducted to test the practicability of the proposed algorithm using images from copy-move databases and to evaluate its robustness against post-processing methods such as additive white Gaussian noise (AWGN), Gaussian blurring, and JPEG compression. The results of experiments show that the proposed scheme effectively detects both copied region and pasted region of forged images and that it is robust to the post-processing methods mentioned above.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.47-57
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• 2019

We examine the weaknesses of the existing OOXML-based MS-Word file structure, and analyze how data concealment and forgery are performed in MS-Word digital documents. In case of forgery by including hidden information in MS-Word digital document, there is no difference in opening the file with the MS-Word Processor. However, the computer system may be malfunctioned by malware or shell code hidden in the digital document. If a malicious image file or ZIP file is hidden in the document by using the structural vulnerability of the MS-Word document, it may be infected by ransomware that encrypts the entire file on the disk even if the MS-Word file is normally executed. Therefore, it is necessary to analyze forgery and alteration of digital document through internal structure analysis of MS-Word file. In this paper, we designed and implemented a mechanism to detect this efficiently and automatic detection software, and presented a method to proactively respond to attacks such as ransomware exploiting MS-Word security vulnerabilities.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.457-466
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• 2010

In this paper, we propose a new method for detecting digital forgery that identify interpolated region between digital composited images. For detecting the interpolation factor and the tampered regions, we perform two algorithms: The first algorithm is to estimate the interpolation factors using the differential equation for forgery image along the horizontal, vertical, and diagonal directions, respectively; The second algorithm is to scan the interpolation factors along each direction for detection areas as the mask of the optical window size($64{\times}64$) in order to find out the forgery region. A detection map of the forgery is classified with the magnitude of estimated interpolation factors into colors. This detection map can be used to find out interpolated regions from the tampered image. Experimental results demonstrate the proposed algorithms are proven on several examples. We also show the proposed approach is to accurately detect interpolated regions from digital composite images.

• Convergence Security Journal
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• v.16 no.1
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• pp.81-87
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• 2016

In this paper, we propose a forgery/falsification detection technique of web site using the images. The proposed system captures images of the web site when a user accesses to the forgery/falsification web site that has the financial information deodorizing purpose. The captured images are compared with those of normal web site images to detect forgery/falsification. The proposed system calculates similarity factor of normal site image with captured one to detect whether the site is normal or not. If it is determined as normal, analysis procedure is finished. But if it is determined as abnormal, a message informs the user to prevent additional financial information spill and further accidents from the forgery web site.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.667-670
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• 2013

Noise is unwanted in high quality images, but it can aid image tampering. For example, noise can be intentionally added in image to conceal tampered regions or to create special visual effects. It may also be introduced unknowingly during camera imaging process, which makes the noise levels inconsistent in splicing images. In this paper, we present an image forgery detection method using a noise dependent watershed transformation. Image is segmented into objects for initial noise estimation by the watershed transformation, and different noise level in objects are estimated to obtain final decision result. Experimental results of the proposed method on natural images are presented.

• Journal of Biomedical Engineering Research
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• v.23 no.2
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• pp.81-85
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• 2002

In this paper, a new fragi1e watermarking algorithm for medical images is proposed. It makes possible to resolve the security and forgery problem of the medical images. In the proposed algorithm. the singularity which represents the inherent characteristic of the medical image is extracted and used as watermark. To extract the singularity point. we adopted Mallat wavelet transform because it can describe the edge of image exactly. Mallat wavelet transform produces horizontal and vertical subbands of the same resolution with the original image. The magnitude and phase components of the edge are obtained using these subbands. Based on the magnitude and phase components. LMM which will be used as watermark is determined. As LMM is the inherent singularity of image, if any forgery is applied to medical image, LMM of original and forged image are different each other Detecting the changes of LMM for the two images makes it possible whether any image is undergone forgery or not From the experimental results, we conformed that the proposed algorithm detects the forged area of the image very well.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.5
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• pp.163-172
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• 2014

The Scale Invariant Feature Transform (SIFT) has been widely used in a lot of applications for image feature matching. Such a transform allows us to strong matching ability, stability in rotation, and scaling with the variety of different scales. Recently, it has been made one of the most successful algorithms in the research areas of copy-move forgery detections. Though this transform is capable of identifying copy-move forgery, it does not widely address the possibility that counter-forensics operations may be designed and used to hide the evidence of image tampering. In this paper, we propose a targeted counter-forensics method for impeding SIFT-based copy-move forgery detection by applying a semantically admissible distortion in the processing tool. The proposed method allows the attacker to delude a similarity matching process and conceal the traces left by a modification of SIFT keypoints, while maintaining a high fidelity between the processed images and original ones under the semantic constraints. The efficiency of the proposed method is supported by several experiments on the test images with various parameter settings.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.42-47
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• 2017

In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.