• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.63-65
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• 2017

This paper proposes a detection algorithm of video tampering by investigating the change of HEVC coding pattern. When a part of video is deleted and re-compressed, the characteristic patterns are generated by forgery. The proposed algorithm uses these patterns to classify whether video is forged. Experimental results show that the proposed method detects video forgery effectively.

• Journal of KIISE
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• v.45 no.3
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• pp.311-320
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• 2018

Recently, the use of digital audio and video as proof in criminal and all kinds of litigation is increasing, and scientific investigation using digital forensic technique is developing. With the development of computing and file editing technologies, anyone can simply manipulate video files, and the number of cases of manipulating digital data is increasing. As a result, the integrity of the evidence and the reliability of the evidence Is required. In this paper, we propose a technique for extracting the Electrical Network Frequency (ENF) through a grid of power grids according to the geographical environment for power supply, and then performing signal processing for peak detection using QIFFT. Through the detection algorithm using the standard deviation, it was confirmed that the video file was falsified with 73% accuracy and the forgery point was found.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.734-743
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• 2017

In this paper, we introduce a technique to detect the video forgery using coding pattern analysis. In the proposed method, the recently developed standard HEVC codec, which is expected to be widely used in the future, is used. First, HEVC coding patterns of the forged and the original videos are analyzed to select the discriminative features, and the selected feature vectors are learned through the machine learning technique to model the classification criteria between two groups. Experimental results show that the proposed method is more effective to detect frame deletions for HEVC-coded videos than existing works.

• Annual Conference of KIPS
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3943-3957
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• 2016

As digital evidence has a highly influential role in proving the innocence of suspects, methods for integrity verification of such digital evidence have become essential in the digital forensic field. Most surveillance camera systems are not equipped with proper built-in integrity protection functions. Because digital forgery techniques are becoming increasingly sophisticated, manually determining whether digital content has been falsified is becoming extremely difficult for investigators. Hence, systematic approaches to forensic integrity verification are essential for ascertaining truth or falsehood. We propose an integrity determination method that utilizes the structure of the video content in a Video Event Data Recorder (VEDR). The proposed method identifies the difference in frame index fields between a forged file and an original file. Experiments conducted using real VEDRs in the market and video files forged by a video editing tool demonstrate that the proposed integrity verification scheme can detect broken integrity in video content.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3238-3257
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• 2019

Closed-circuit television (CCTV) technology continuously captures and stores video streams. Users are typically required by policy to store all the captured video for a certain period. Accordingly, increasing the number of CCTV operation cycles and photographing positions expands the amount of data to be stored. However, expanding the available storage space for video data incurs increased costs. In recent years, this problem has been addressed with cloud storage solutions, which enable multiple users and devices to access and store data simultaneously. However, because of the large amount of data to be stored, a vast storage space is required. Consequently, cloud storage administrators need a way to store data more efficiently. To save storage space, deduplication technology has been proposed to prevent duplicate storage of the same data. However, because cloud storage is hosted on remote servers, data encryption technology must be applied to address data exposure issues. Although deduplication techniques for encrypted data have been studied, there have been various security vulnerabilities. We attempted to solve this problem by addressing various issues such as poison attacks, property forgery, and ownership management while removing the redundant data and handling the data more securely.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.794-799
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• 2008

This paper presents a user identification method at H.264 streaming using watermarking with fingerprints. The watermark can efficiently reduce the potential danger of forgery or alteration. Especially a biometric watermark has convenient, economical advantages. The fingerprint watermark can also improve reliability of verification using automated fingerprint identification systems. These algorithms, however, are not robust against common video compression. To overcome this problem, we analyze H.264 compression pattern and extract watermark after restoring damaged watermark using various filters. The proposed algorithm consists of enhancement of a fingerprint image, watermark insertion using discrete wavelet transform and extraction after restoring. The proposed algorithm can achieve robust watermark extraction against H.264 compressed videos.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.886-895
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• 2018

In this paper, we introduce a technique to detect the video forgery by using the regularity that occurs in the video compression process. The proposed method uses the hierarchical regularity lost by the video double compression and the frame deletion. In order to extract such irregularities, the depth information of CU and TU, which are basic units of HEVC, is used. For improving performance, we make a depth map of CU and TU using local information, and then create input data by grouping them in GoP units. We made a decision whether or not the video is double-compressed and forged by using a general three-dimensional convolutional neural network. Experimental results show that it is more effective to detect whether or not the video is forged compared with the results using the existing machine learning algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.662-675
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• 2018

Compression history detection plays an important role in digital multimedia forensics. Most existing works, however, mainly focus on digital image and video. Additionally, the existed audio compression detection algorithms aim to detect the trace of double compression. In real forgery scenario, multiple compression is more likely to happen. In this paper, we proposed a detection algorithm to reveal the compression history for MP3 audio. The statistics of the scale factor and Huffman table index which are the parameters of MP3 codec have been extracted as the detecting features. The experimental results have shown that the proposed method can effectively identify whether the testing audio has been previously treated with single/double/triple compression.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.535-539
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• 2008

With the advancement which development and information communication of the computer is quick about lower with multimedia technical diffusion of network base the necessity the use of the digital image technique which is various regarding the protection of sharp increasing multimedia contents raised its head in the social whole. The copyright protection against a multimedia data hazard the authentication techniques it will be able to confirm the content authentication, ownership authentication, illegal copy of the image which stands is demanded. confronts to the water marking technique of existing and the researches the fact that against a picture is most. In this paper, It does not damage the video data. As inserts copyright information and it protects the copyright. It is with a copyright protection which leads the wavelet transform which is a watermark of frequency base from visual system viewpoint in the human being center with it proposes the watermarking technique against a forgery prevention.