• 전자공학회논문지
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• 제52권8호
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• pp.67-73
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• 2015

디지털 영상의 배포에서, 위 변조자에 의해 영상이 변조되는 심각한 문제가 있다. 이러한 문제를 해결하기 위하여, 본 논문에서는 영상의 Fourier 변환 변이계수를 이용한 미디언 필터링 (Median Filtering: MF) 영상의 포렌식 판정 알고리즘을 제안한다. 제안된 알고리즘에서, 영상의 각 수평, 수직라인의 Fourier 변환 (Fourier Transform: FT)을 하고, 이웃 라인과의 변이계수를 기반으로 하여 MF 검출 (Median Filtering Detection: MFD)을 위한 10 Dim. 특징벡터를 정의한다. 이는 MF 검출기의 SVM (Support Vector Machine) 학습에 사용된다. 제안된 미디언 필터링 검출 스킴은 동일 10 Dim. 특징벡터의 MFR (Median Filter Residual)과 Rhee의 MF 검출 스킴과 비교하여 원영상, JPEG (QF=90), Down 스케일링 (0.9) 그리고 Up 스케일링 (1.1) 영상에서는 성능이 우수하며, Gaussian 필터링($3{\times}3$) 영상에서는 성능이 일부 높았다. 제안된 알고리즘은 성능평가 전체항목에서 민감도 (Sensitivity; TP: True Positive rate)와 1-특이도 (1-Specificity; FP: False Positive rate)에 의한 AUC (Area Under ROC (Receiver Operating Characteristic) Curve)가 모두 1에 수렴하여 'Excellent (A)' 등급임을 확인하였다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2019년도 추계학술대회
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• pp.58-60
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• 2019

Double JPEG compression detection is one of the most important ways of exposing the integrity of the JPEG image in image forensics. Several methods have been proposed for discriminating against the double JPEG image. In this paper, we propose a new method for restoring the JPEG compressed image and making the detector confused by introducing a Generative Adversarial Network (GAN). First, a generator network is designed for restoring the JPEG compressed image and analyzed the quality. Then, the restored image is tested with the double compression detector for evaluating the robustness of the proposed GAN model. The detection accuracy reduces from 98% to 58%.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제6권2호
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• pp.75-86
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• 2017

오늘날 다양한 서버 내 가상화 기술 중 도커(Docker)는 기존의 방식보다 경량화된 서비스 운영 환경을 제공함으로써 많은 기업 환경에 도입되고 있다. 도커는 이미지, 컨테이너 개념을 통해 서버 환경 구축, 업데이트, 이동을 효율적으로 할 수 있게 지원한다. 도커가 많이 보급될수록 도커 이미지를 배포하는 서버나 도커 기반의 호스트에 대한 공격 유인이 증가할 것이다. 이에 본 논문에서 도커 데몬이 비활성화 된 상태에서도 컨테이너의 파일 시스템을 추출할 수 있는 방안을 포함하여 도커를 사용하는 호스트에 대한 포렌식 조사 기법과 그 절차를 제시하였다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(C)
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• pp.245-247
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• 2012

We know that JPEG image format is one of the most popular image formats in the digital area and distribution of digital photographic drawing it is interested frequently in certain types of forensic investigation. In most case, corrupted images are shown gaudiness with the boundary of the corrupted parts. In the paper, we propose a technique to carve correct JPEG images using transformation method and the approach can be used for JPEG image file carving tool development.

• Imaging Science in Dentistry
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• 제51권2호
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• pp.187-193
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• 2021

Purpose: This study aimed to assess the usefulness of machine learning and automation techniques to match pairs of panoramic radiographs for personal identification. Materials and Methods: Two hundred panoramic radiographs from 100 patients (50 males and 50 females) were randomly selected from a private radiological service database. Initially, 14 linear and angular measurements of the radiographs were made by an expert. Eight ratio indices derived from the original measurements were applied to a statistical algorithm to match radiographs from the same patients, simulating a semi-automated personal identification process. Subsequently, measurements were automatically generated using a deep neural network for image recognition, simulating a fully automated personal identification process. Results: Approximately 85% of the radiographs were correctly matched by the automated personal identification process. In a limited number of cases, the image recognition algorithm identified 2 potential matches for the same individual. No statistically significant differences were found between measurements performed by the expert on panoramic radiographs from the same patients. Conclusion: Personal identification might be performed with the aid of image recognition algorithms and machine learning techniques. This approach will likely facilitate the complex task of personal identification by performing an initial screening of radiographs and matching ante-mortem and post-mortem images from the same individuals.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1886-1898
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• 2015

In today’s era of advanced technological developments, the threats to the authenticity and integrity of digital images, in a nutshell, the threats to the Image Forensics Research communities have also increased proportionately. This happened as even for the ‘non-expert’ forgers, the availability of image processing tools has become a cakewalk. This image forgery poses a great problem for judicial authorities in any context of trade and commerce. Block matching based image cloning detection system is widely researched over the last 2-3 decades but this was discouraged by higher computational complexity and more time requirement at the algorithm level. Thus, for reducing time need, various dimension reduction techniques have been employed. Since a single technique cannot cope up with all the transformations like addition of noise, blurring, intensity variation, etc. we employ multiple techniques to a single image. In this paper, we have used Fuzzy logic approach for decision making and getting a global response of all the techniques, since their individual outputs depend on various parameters. Experimental results have given enthusiastic elicitations as regards various transformations to the digital image. Hence this paper proposes Fuzzy based cloning detection and classification system. Experimental results have shown that our detection system achieves classification accuracy of 94.12%. Detection accuracy (DAR) while in case of 81×81 sized copied portion the maximum accuracy achieved is 99.17% as regards subjection to transformations like Blurring, Intensity Variation and Gaussian Noise Addition.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1624-1631
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• 2021

With the continued development of image processing technology, we live in a time when it is difficult to visually discriminate processed (or tampered) images from real images. However, as the risk of fake images being misused for crime increases, the importance of image forensic science for identifying fake images is emerging. Currently, various deep learning-based identifiers have been studied, but there are still many problems to be used in real situations. Due to the inherent characteristics of deep learning that strongly relies on given training data, it is very vulnerable to evaluating data that has never been viewed. Therefore, we try to find a way to improve generalization ability of deep learning-based fake image identifiers. First, images with various contents were added to the training dataset to resolve the over-fitting problem that the identifier can only classify real and fake images with specific contents but fails for those with other contents. Next, color spaces other than RGB were exploited. That is, fake image identification was attempted on color spaces not considered when creating fake images, such as HSV and YCbCr. Finally, dropout, which is commonly used for generalization of neural networks, was used. Through experimental results, it has been confirmed that the color space conversion to HSV is the best solution and its combination with the approach of increasing the training dataset significantly can greatly improve the accuracy and generalization ability of deep learning-based identifiers in identifying fake images that have never been seen before.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제6권7호
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• pp.307-314
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• 2017

스틱-PC(Stick-PC)는 크기가 작고 휴대가 용이하여 언제 어디서든 모니터나 TV 등의 디스플레이 장치에 연결하면 데스크탑 PC(Desktop PC)처럼 사용이 가능하다. 이에 따라 스틱-PC(Stick-PC)도 일반 PC처럼 각종 범죄로 연결될 수 있으며 다양한 증거들이 남아 있을 수 있다. 스틱-PC(Stick-PC)는 일반 데스크탑 PC(Desktop PC)와 같은 윈도우즈(Windows) 버전의 운영체제를 사용하고 있어 분석해야 할 아티팩트들은 동일하다. 하지만 데스크탑 PC(Desktop PC)와 달리 이동성이 있어 시스템 분석 전에 주변 기기 연결 흔적을 찾아 실사용자 확인 및 사용 흔적을 파악하는 것이 이루어지면 포렌식 조사 시 상당히 의미 있는 정보로 사용될 수 있다. 따라서 본 논문은 스틱-PC(Stick-PC)의 이미지 수집 방법 중 하나인 Bootable OS를 이용하여 이미지를 수집하는 방법을 제시한다. 또한 레지스트리와 이벤트로 그를 통해 디스플레이, 블루투스(Bluetooth) 등의 주변기기 연결 흔적과 네트워크 연결 흔적을 분석하는 방법을 제시하고 실험 시나리오를 통해 포렌식 관점에서 활용 방안을 제시한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.287-290
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• 2003

Over the last few years computer based image processing has become more prominent in forensic science. The image quality from many CCTV systems is too poor for facial recognition. but there are other human characteristics which allow us to recognize individuals from a distance. one of these parameters is a human's height. In this paper, we propose useful height measurement method by auto Position, size adjustment which uses image superimposition and edge detection regardless of lens distortion and not uses conventional photogrammetry calibration methods.

• Bulletin of the Korean Chemical Society
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• 제32권4호
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• pp.1387-1390
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• 2011