Earticle

In Fragmented JPEG carving we require header information for a successful recovery of the image. In case of a fragment with a corrupted or missing header we need a way to extract important parameters from the content of the blocks. In this paper the inter block mean absolute difference is proposed to detect the size information of the JPEG fragment. The proposed approach has improved the complexity of the existing image size extraction approach to O(n), moreover we are able to get offset information of the block arrangement in the fragment.

우리는 자동차 2천만시대에 살고 있으며 이는 인구 2인당 1대 이상인 셈이다. IOT, AI, vision 기술 등 이 빠르게 발전하고 있으나 우리는 아직도 아날로그 자동차 번호를 사용하고 있다. 그에 따라 자동차 번호판을 위 조한 각종 범죄(과속, 하이패스 무단통과, 불법 주정차 등)가 발생하고 있으며 과태료가 죄가 없는 차량 소유주에 게 전달되고 있다. 자동차 번호판은 아날로그 형태로 되어 있으며 이를 인식하는 장치는 카메라를 이용한 화상인 식 시스템에 의존하고 있다 보니 위조를 적발해내기가 용이하지 않다. 따라서 본 논문에서는 현재의 아날로그 형 태의 자동차 번호판을 디지털 형태로 변경하지 않고서도 위조를 검출해낼 수 있는 방법을 제안하고자 한다. 제안 하는 방법은 기존의 단속 시스템의 변경을 최소화하며 신속하게 위조를 적발하여 더 이상 선의의 피해자가 나오지 않도록 하게 한다.

There are 20 million cars, which means there are more than one vehicle for two person. Advanced technologies, such as the Internet of Things (IoT), artificial intelligence (AI), vision, etc. have rapidly progressed; however, analog car numbers are still being used. As a result, various crimes with forged license plates such as speeding, unauthorized high-pass, and illegal parking are occurring. With this, the innocent vehicle owner may be unfairly burdened with the fine. The license plate of a vehicle is in analog form and the most image recognition system utilizes a camera to recognize a vehicle's license plate, which in turn makes the detection of forgery challenging. Therefore, this paper proposes a method to detect forgery in vehicle plates without transforming an analog plate into a digital format. The proposed method is expected to minimize changes to the existing enforcement system, quickly detect forgery, and therefore prevent any further victims who may be acting in good faith.

Audio recordings are used widely as crucial evidence due to the popularity of smartphones. However, the digital evidence submitted voluntarily may be questioned for its authentication. Since most smartphones provide the function of digital editing files, they could be exposed to crime as being edited maliciously. Primarily, it could be severe in the case of voluntary submission via information and communications networks. This paper proposed the forensic method for authentication of audio recordings generated by the Voice Recorder application from Samsung smartphones. First, we analyzed and compared the file structures and timestamps of audio recordings between the normal state without manipulation and the manipulated state. Then, we analyzed the spectrogram of audio recordings. Finally, by analyzing the timestamps of the media-log for audio recordings, we confirmed the authentication method for the audio recordings forensically.

Copy-Move-Forgery (CMF) is one of the common ways of tampering digital images. Forging an image has become very easy and visually confusing to detect it from the authentic one. Broadly speaking, CMF detection methods generally use either block-based or feature point-based approaches. In this paper, we proposed a new technique called keypoint based Circle-Block model in which first keypoints are extracted; then Circle-blocks are constructed centering the keypoints. Block matching is made using color and pixels behavior of the blocks.

Digital image forgery has become a serious problem due to the sophistication and accessibility of image editing software. Copy move forgery is the simplest type of forgery that involves copying portion of an image and paste it on different location within the image. There are many approaches to detect copy paste forgery, but all of them have their own limitations. In this paper visual and invisible feature based forgery detection techniques are compared and contrasted. The analysis shows that pros and cons of these two techniques compensate each other. Therefore, a hybrid of visual based and invisible feature based forgery detection that combine the merits of both techniques is proposed. The experimental results shows that the proposed algorithm has enhanced performance compared to individual techniques. Moreover, it provides more information about the forgery, like identifying copy and duplicate regions.

본 논문에서는 이미지를 이용한 웹사이트 위·변조 탐지 기법을 제안한다. 제안하는 시스템은 사용자가 웹사이트 위· 변조를 통한 금융정보 탈취 목적을 가진 악성코드에 감염된 후 특정 금융 웹사이트에 접속 시 사용자가 접속한 웹사이 트의 캡처 이미지와 정상 웹사이트의 캡처 이미지의 유사도를 비교분석하여 웹사이트 위·변조 여부를 탐지하고 정상인 경우 분석을 종료하지만 비정상으로 판단될 경우 이를 사용자에게 메시지를 통해 현재의 피해 상태를 알려줌으로써 위·변조된 웹사이트를 통해서 추가적인 금융정보 유출 사고가 발생하지 않도록 사전에 방지한다.

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

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.

Forgery detection techniques are required to verify the authenticity of the digital images. The additional noise is the most general way to hide the traces of the tampering done to the image. Original images which do not undergo any alterations are supposed to have a consistency in noise variation. If the image is forged, the noise no longer remains consistent throughout the image. In this paper, a method is proposed to detect the forgery based upon noise estimation and hog feature extraction. The image is first converted to YIQ colorspace, and then the block segmentation is performed on Y component of the YIQ image. Noise is estimated using PCA and hog features are extracted from each block of the image. An unsupervised clustering method is used to cluster the blocks of the image. The experimental results show that the proposed technique detects forged images more effectively as compared to previous method based only on noise estimation.

In order to solve such problems as poor robustness and low detection accuracy in the present copying & pasting forgery detection algorithm, an image copying & moving forgery detection algorithm based on non-sampling wavelet transform (undecimated wavelet transform, UWT) coupling with Zernike moments is proposed in this article. Firstly, the non-sampling wavelet transform is adopted to decompose the input image into approximation coefficient LL and detail coefficient HH to obtain the similarity and the diversity of the image blocks; secondly, the overlapped blocks are divided to calculate the sub-block interval of the image; thirdly, the sub-blocks are ordered and classified according to LL similarity and HH diversity; fourthly, Zernike moments are introduced to construct the distance matrix for image feature matching and image forgery detection. The experiment shows: the algorithm proposed thereby has good translation invariance and amplitude rotation invariance, good post-processing resistance performance, high detection accuracy, low false negative rate and low false positive rate.

The development of powerful image editing software has made it easy to create visually convincing digital image forgeries. Recently some research works based on general low-level visual features in the field of digital image forensics have been conducted to address this problem. However, there has been little work by analyzing the high-level semantic content of the image. This paper discusses the forgery detection problem of digital image from the point of high-level semantic, and proposes the framework of image forgery detection based on semantics. The framework consists of three components including image recognition, semantic logic reasoning engine and generation of semantic rule. A new fuzzy logic semantic reasoning model for image forgery detection is proposed in this paper. Our reasoning model based on fuzzy logic can give the deterministic and uncertainty reasoning results. Based on the proposed framework of image forgery detection, the prototype system of image forgery detection based on semantics is completed using MATLAB, MySQL database software and ontology software protégé and has the ability to detect abnormal splicing from the foreground and background, avoiding detection using the traditional methods based on low-level image features. Experimental results show that the framework and logic semantic reasoning model for image forgery detection are effective.

There are some applications of military and e-commerce networks, where security of transmitted data on unfriendly environment requires more concern as compared to other design issues like power and energy consumption. Data alterations in above mentioned applications can lead to irreparable losses; so to avoid such losses, we have to maintain Data Integrity in the communication network. This paper presents a novel and reliable Hash algorithm which inherits the basic architecture of SHA-1. Performance of proposed technique is compared with existing techniques through statistical test suite for random numbers. Results reveal that the suggested technique is more effective in terms of randomness than the existing algorithms. The proposed technique, thus, finds its applicability in the sensitive data environment.

Digital images are inseparable part of our life. Images are used at various places like medical imaging, crime scene investigation, forensic analysis, courts etc. but due to ubiquitous accessibility of image editing software, images are no longer trusted. Digital images are losing their credibility. For checking authenticity of digital images forgery detection methods are required. One of the most frequent image forgery is copy-move. In this forgery, a region of the original image is used for producing a manipulated image by performing post-processing operations over copied segment before pasting it to original image. The main principle of finding such type of forgery is based on finding resemblance present in different segments of image. Image is divided in blocks then feature vectors are extracted corresponding to different blocks of image. Sorting techniques are applied to find similarity between blocks. In case of natural images which may have similar regions, shift vectors are calculated to decrease false matches. Several methods are suggested by researchers to detect such type of forgery. In this paper, a survey on frequency-based methods is presented for detecting copy-move forgery in images.

With the rapid development and popularization of Photoshop, ACDSee and other digital processing and editing software, the non-professionals can easily modify the image to achieve the purpose of beautification, spoof or malicious tampering. Digital tampering usually has ulterior motives, which would bring crisis of confidence to the credibility of media image, the authenticity of judicial evidence and the reliability of military intelligence. The Copy-move forgery is one of the most common and immediate tampering attacks, and is one type of image forgery where one region of an image is copied to another region in an attempt to cover some potentially important features. In this paper, an efficient algorithm is presented for image copy-move forgery detection and localization based on DWT and SVD. Experiment results demonstrate that our proposed algorithm can effectively detect multiple copy-move forgery and precisely locate the duplicated regions, even when an image was distorted by Gaussian blurring, JPEG compression and their mixed operations.

With the widespread use of powerful image editing tools, the demand for identifying the authenticity of an image is much increased. Copy-move forgery is one of the most common and immediate tampering attacks, and is one type of image forgery where one region of an image is copied to another region in an attempt to cover some potentially important features. In this paper a Novel approach is presented for image copy-move forgery detection and localization based on SVD and Projection Data. Experiment results demonstrate that our proposed algorithm can effectively detect multiple copy-move forgery and precisely locate the duplicated regions, even when an image was distorted by Gaussian blurring,JPEG compression and their mixed operations.

Offline signature verification system finds several applications in monitory transaction systems like banks. However one of the major challenges in this direction is the capability of the system to detect skilled and unskilled forgery. Many cases of bank check forgeries have been reported. Most of the offline signature verification system adopts recognition based technique where the system classifies a given signature sample as one of the samples from the database. However detection of a forgery in a given sample is challenging as the input sample looks similar to one of the samples in the database. In this paper we propose an innovative approach for offline signature verification with polar feature descriptor for signature that contains Radon Transform and Zernike Moments. Verification is performed using Multiclass Support Vector Machine. Once a signature is verified as being of a registered class, PLS Regression is applied on the sample against all samples in the database of the verified user to obtain regression score. Log Likelihood of the sample against all sample of the user is calculated using Hidden Markov Model. Authenticity of the classification is justified if the regression score and Log Likelihood distance deviation is less than 5%. Results show that the system verifies signature with an accuracy of 98% with false acceptance rate of .8%. Proposed system also detects skilled forgery with an accuracy of 71% and Random forgery with an accuracy of 76%.

In this paper, we proposed a new fast detection method of copy-move forgery image using two step search algorithm in the spatial domain. We proposed a new two step search algorithm for copy-moved forgery image detection. The performance of the proposed method is experimented on several forged images. Our two step search algorithm reduced 96.82% computational complexity more than conventional algorithms for copy-move forgery image detection. The block distortion measure (BDM) of the two step search algorithm is sufficient by 2 pixels checking points instead of 64 pixels checking points for exhaustive search in the not copy-moved forgery image regions. Most blocks of the images constitute not copy-moved forgery images. Therefore, we can reduce computational complexity more than conventional methods. We didn’t use any exhaustive search method and frequency domain (ex. DCT, Wavelet Transform) to reduce computational complexity in this paper.

오늘날 누구나 디지털 정보를 용이하게 활용할 수 있게 됨에 따라 디지털 증거의 채택이 증가되고 있다. 하지 만 다양한 음성 파일 편집 도구를 보급과 함께 정교한 편집 과정을 거친 음성 녹음 파일의 경우 위변조 진위 여부를 판 단하는 것은 사실상 불가능하다. 본 연구는 음성 녹음 파일에 삽입, 삭제, 연결 및 합성 편집 기술을 활용해 원본 파 일과 구별하기 어려운 위변조가 가능함을 증명하고자 한다. 본 연구는 위변조 된 음성 파일을 원본과 동일한 확장자 로 인코딩하는 작업을 통해 위변조 검출의 어려움을 제시한다. 또한 특징점이 발생한 실험에 한 하여 추가적으로 천 이대역의 삭제 및 2차 인코딩 작업을 수행할 경우 위변조 검출은 불가능함을 나타냈다. 이를 통해 본 연구는 음성 녹 음 파일을 디지털 증거로 채택하기 위한 더 엄격한 증거능력 판단 기준 수립에 공헌할 것으로 기대된다.

As digital information is readily available to everyone today, the adoption of digital evidence is increasing. However, it is virtually impossible to determine the authenticity of forgery in the case of a voice recording file that has gone through a sophisticated editing process along with the spread of various voice file editing tools. This study aims to prove that forgery, which is difficult to distinguish from the original file, is possible by using insertion, deletion, linking, and synthetic editing technologies in voice recording files. This study presents the difficulty of detecting forgery by encoding a forged voice file with the same extension as the original. In addition, it was shown that forgery detection is impossible if additional transition band deletion and secondary encoding are performed only for experiments in which features occurred. Through this, this study is expected to contribute to the establishment of more stringent evidence admissibility criteria for adopting voice recording files as digital evidence.