• Journal of Korea Multimedia Society
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• v.15 no.2
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• pp.179-194
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• 2012

Digital image forgery is becoming a topic of great interest with regard to honesty in imaging. We can often see forged digital images in a variety of places, such as the internet, and magazines, and in images used in political ads, etc. These can reduce the reliability and factual basis of the information contained in image. Therefore, objectivity is needed to determine if the image is forged so as to prevent confusion in the viewing public. Most digital forgeries consist of image resizing, rotating including the following interpolations. To find evidence of interpolation in forged images, this paper proposes a new method for detecting digital image forgery using general interpolation factors analyzed through re-interpolation algorithm of the forged images in order to determine the differences in the patterns. Through the re-interpolation algorithm we could detect the forged region and filtering region used image retouching included to interpolation.

• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.39-47
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• 2005

This paper proposes and analyzes the MAC(Message Authentication Code) algorithm that is used for the transition integrity and the entity authentication of message. The MAC algorithm uses the DES algorithm which has 64-bit block and 56-bit key and we compare the security according to 64-bit and 32-bit length of MAC value. Moreover, we use the SEED algorithm which has 128-bit block and 128-bit key and compare the security according to 128-bit and 64-bit length of MAC value. We analyze the security the forgery attack according to length of message and length of MAC value. this paper, a coarse-to-fine optical flow detection method is proposed. Provided that optical flow gives reliable approximation to two-dimensional image motion, it can be used to recover the three-dimensional motion. but usually to get the reliable optical flows are difficult. The proposed algorithm uses Horn's algorithm (or detecting initial optical flow, then Thin Plate Spline is introduced to warp a image frame of the initial optical flow to the next image frame. The optical flow for the warped image frame is again used iteratively until the mean square error between two image sequence frames is lowered. The proposed method is experimented for the real moving Picture image sequence. The proposed algorithm gives dense optical flow vectors.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.136-144
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• 2022

Construction sites are characterized by dangerous situations and environments that cause fatal accidents. Potential risk detection needs to be improved by continuously monitoring site conditions. However, the current labor-intensive inspection practice has many limitations in monitoring dangerous conditions at construction sites. Computer vision technology that can quickly analyze and collect site conditions from images has been in the spotlight as a solution. Nonetheless, inspection results obtained via computer vision are still stored and managed in centralized systems vulnerable to tampering with information by the central node. Blockchain has been used as a reliable and efficient decentralized information management system. Despite its potential, only limited research has been conducted integrating computer vision and blockchain. Therefore, to solve the current safety management problems, the authors propose a framework for construction site inspection that integrates object detection and blockchain network, enabling efficient and reliable remote inspection. Object detection is applied to enable the automatic analysis of site safety conditions. As a result, the workload of safety managers can be reduced with inspection results stored and distributed reliably through the blockchain network. In addition, errors or forgery in the inspection process can be automatically prevented and verified through a smart contract. As site safety conditions are reliably shared with project participants, project participants can remotely inspect site conditions and make safety-related decisions in trust.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.77-85
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• 2015

In this paper, we present a new method that can detect forged color region using color pattern decomposition and hypothesis testing approach. On the basis of the fact that the variance of the interpolated pixel is smaller than that of the original pixel, we use a statistical test method to judge the statistical inconsistency of variance. For this, we calculate the variance adopting a color pattern decomposition according to the demosaicking pattern. In addition, we apply high-pass filtering to enlarge the difference between the variances of original and interpolated pixel. Through experimental simulations, we can see that our proposed method can effectively detect forged color regions and shows superior detection performance compared to the conventional method.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.132-146
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• 2020

Biometric technologies have become widely available in many different fields. However, biometric technologies using existing physical features such as fingerprints, facial features, irises, and veins must consider forgery and alterations targeting them through fraudulent physical characteristics such as fake fingerprints. Thus, a trend toward next-generation biometric technologies using behavioral biometrics of a living person, such as bio-signals and walking characteristics, has emerged. Accordingly, in this study, we developed a bio-signal authentication algorithm using electrocardiogram (ECG) signals, which are the most uniquely identifiable form of bio-signal available. When using ECG signals with our system, the personal identification and authentication accuracy are approximately 90% during a state of rest. When using fingerprints alone, the equal error rate (EER) is 0.243%; however, when fusing the scores of both the ECG signal and fingerprints, the EER decreases to 0.113% on average. In addition, as a function of detecting a presentation attack on a mobile phone, a method for rejecting a transaction when a fake fingerprint is applied was successfully implemented.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.250-255
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• 2000

This paper is concerning off-line signature verification using a density function which is obtained by convolving the signature image with twelve-directional 5$\times$5 gradient masks and the weighted fuzzy mean classifier. The twelve-directional density function based on Nevatia-Babu template gradient is related to the overall shape of a signature image and thus, utilized as a feature set. The weighted fuzzy mean classifier with the reference feature vectors extracted from only genuine signature samples is evaluated for the verification of freehand forgeries. The experimental results show that the proposed system can classify a signature whether genuine or forged with more than 98% overall accuracy even without any knowledge of vaned freehand forgeries.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1885-1888
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• 2003

본 논문에서는 인쇄물의 위조방지를 위해 에러에 강한 디지털 워터마킹을 제안한다. 제안한 알고리즘은 워터마크 삽입을 위해 먼저 원영상을 웨이브릿 변환하여 근사(approximation) 이미지를 얻고, 워터마크는 근사 이미지의 DC계수를 제외한 중요한 DCT계수에 삽입된다. 워터마크의 강건도 향상을 위해 에러정정코드와 반복을 적용하고, 디지털 기기사이의 변환에 의한 차이를 줄이기 위해 CIE Lab 칼라 공간을 사용하였다. 표준 칼라 영상을 사용하여 실험한 결과, 기존 방법에 비하여 적은 반복으로도 비트에러가 발생을 감소하였으며, 알고리즘은 1차의 프린트 스캔에서는 robust 하고 2차의 프린트 스캔에서는 fagile 한 성격을 나타내었다, 본 알고리즘은 여권, 지폐, 신분증, 면허증등과 같은 인쇄물의 위조방지에 이용될 수 있다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.65-71
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• 2019

IAs smart device penetration rate is more than 90%, mobile transaction ratio using smart device is increasing. Smart contracts are used in various areas of real life including smart trading. By applying smart contracts to the platform for smart transactions through block-chain technology, the threat of hacking or forgery can be reduced. However, various threats to devices in smart transactions can pose a threat to the use of block chain Etherium, an important element in privilege and personal information management. Smart contract used in block chain Ethereum includes important information or transaction details of users. Therefore, in case of an attack of privilege elevation, it is very likely to exploit transaction details or forge or tamper with personal information inquiry. In this paper, we propose a detection and countermeasure method for privilege escalation attack, which is especially important for block chain for secure smart transaction using block chain Ethereum. When comparing the results of this study with the results of similar applications and researches, we showed about 12~13% improvement in performance and suggested the future countermeasures through packet analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1118-1121
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• 2010

With the advent of cell phone digital cameras, and sophisticated photo editing software, digital images can be easily manipulated and altered. Although good forgeries may leave no visual clues of having been tampered with, they may, nevertheless, alter the underlying statistics of an image. Most digital camera equipped in cell phones employ a single image sensor in conjunction with a color filter array (CFA), and then interpolates the missing color samples to obtain a three channel color image. This interpolation introduces specific correlations which are likely to be destroyed when tampering with an image. We quantify the specific correlations introduced by CFA interpolation, and describe how these correlations, or lack thereof, can be automatically detected in any portion of an image. We show the efficacy of this approach in revealing traces of digital tampering in lossless and lossy compressed color images interpolated with several different CFA algorithms in test cell phones.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1024-1027
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• 2011

본 논문은 HD (High-definition) video, SD (Standard-definition) video, low quality video, handset video, 4 가지 Imaging Device 에 대한 프로파일 분석을 통해 비디오 프레임 상에 나타나는 위 변조를 검사하는 방법을 제안한다. High-definition video, Standard-definition video, low quality video, handset video 에 대한 분석을 하고 각 영상의 특이 점을 파악 하여 분류한 클래스에 대한 프로파일검사를 통해 EM Algorithm 을 이용하여 영상의 위 변조를 검사 하고 영상의 신뢰성을 높인다.