• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.480-484
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• 2005

In this paper, the multiwatermarking method to make it possible to the authentication, modification detection and copyright protection of the digital image was proposed. After the original image is transformed by the DWT(Discrete Wavelet Transform), the encrypted watermark information is embedded into the LSB(Least Significant Bit) of LL band on the low frequence domain for authenticating and detecting modified position in the image. And watermark information is embedded by exchanging the wavelet coefficient for the copyright protection. Thereby, we can authenticate the modification and detect the modified location by extracting the values of LSB on the low frequence domain. And we can perceive the copyright information of original image by extracting the embedded watermark on the high frequence domain.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.628-631
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• 2009

In this paper, we proposed a new authentication method using video that was taken during moving a hand-held camera in front of the face. The proposed method extracted individuality from the obtained image sequences using the parametric eigenspace scheme. Changes of facial appearance through authentication trials draw continuous tracks in the low dimensional igenspace. The similarity between their continuous tracks are calculated by DP-matching to verify their identities. Experimental results confirmed that different motions and persons change the shapes of continuous tracks, so the proposed method could identify the person.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.193-199
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• 2008

In this paper, it is proposed the implementation of face authentication system based on real-time image processing. We described the process implementing the two steps for real-time face authentication system. At first face detection steps, we describe the face detection by using feature of wavelet transform, LoG operator and hausdorff distance matching. In the second step we describe the new dual-line principal component analysis(PCA) for real-time face recognition. It is combines horizontal line to vertical line so as to accept local changes of PCA. The proposed system is affected a little by the video size and resolution. And then simulation results confirm the effectiveness of out system and demonstrate its superiority to other conventional algorithm. Finally, the possibility of performance evaluation and real-time processing was confirmed through the implementation of face authentication system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6152-6168
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• 2017

Recently, the biometric-based authentication systems such as FIDO (Fast Identity Online) are increased in mobile computing environments. The biometric-based authentication systems are performed on the mobile devices with the battery, the improving energy efficiency is important issue. In the case, the size of images (i.e., face, fingerprint, iris, and etc.) affects both recognition accuracy and energy consumption, and hence the tradeoff analysis between the both recognition accuracy and energy consumption is necessary. In this paper, we propose an energy-efficient way to authenticate based on biometric information with tradeoff analysis between the both recognition accuracy and energy consumption in multimedia IoT (Internet of Things) transmission environments. We select the facial information among biometric information, and especially consider the multicore-based mobile devices. Based on our experimental results, we prove that the proposed approach can enhance the energy efficiency of GABOR+LBP+GRAY VALUE, GABOR+LBP, GABOR, and LBP by factors of 6.8, 3.6, 3.6, and 2.4 over the baseline, respectively, while satisfying user's face recognition accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.31-38
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• 2017

With the Development of Information Technology, Security is becoming very Important. Existing Security Systems are Mostly Expensive and Not Easy to Implement, and are Also very Complex when using Biometric Information. In this paper, We try to solve this Problem by Implementing a Low cost Internet based Security Terminal Using Fingerprint and Face Image. To Implement a Low-cost Security System, a Fingerprint Scanner and a Camera are installed in Raspberry pi, and the Scanned Image is encrypted with the AES-256 Algorithm and Transmitted to Cloud. Through This Study, We confirmed the Possibility of the Proposed System in view of Authentication, Cost Reduction, Security and Scalability.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.904-919
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• 2019

Many security systems rely solely on solutions based on Artificial Intelligence, which are weak in nature. These security solutions can be easily manipulated by malicious users who can gain unlawful access. Some security systems suggest using fingerprint-based solutions, but they can be easily deceived by copying fingerprints with clay. Image-based security is undoubtedly easy to manipulate, but it is also a solution that does not require any special training on the part of the user. In this paper, we propose a multi-factor security framework that operates in a three-step process to authenticate the user. The motivation of the research lies in utilizing commonly available and inexpensive devices such as onsite CCTV cameras and smartphone camera and providing fully secure user authentication. We have used technologies such as Argon2 for hashing image features and physically unclonable identification for secure device-server communication. We also discuss the methodological workflow of the proposed multi-factor authentication framework. In addition, we present the service scenario of the proposed model. Finally, we analyze qualitatively the proposed model and compare it with state-of-the-art methods to evaluate the usability of the model in real-world applications.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• ETRI Journal
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• v.43 no.1
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• pp.109-119
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• 2021

Self-recovery is a tamper-detection and image recovery methods based on data hiding. It generates two types of data and embeds them into the original image: authentication data for tamper detection and reference data for image recovery. In this paper, a region-based scalable self-recovery (RSS) method is proposed for salient-object images. As the images consist of two main regions, the region of interest (ROI) and the region of non-interest (RONI), the proposed method is aimed at achieving higher reconstruction quality for the ROI. Moreover, tamper tolerability is improved by using scalable recovery. In the RSS method, separate reference data are generated for the ROI and RONI. Initially, two compressed bitstreams at different rates are generated using the embedded zero-block coding source encoder. Subsequently, each bitstream is divided into several parts, which are protected through various redundancy rates, using the Reed-Solomon channel encoder. The proposed method is tested on 10 000 salient-object images from the MSRA database. The results show that the RSS method, compared to related methods, improves reconstruction quality and tamper tolerability by approximately 30% and 15%, respectively.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.187-190
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• 2012

This paper proposes an one-time authentication system for web applications by making use of the quick-response code, which is widely used nowadays. The process is not time-consuming. It does not require any browser extensions or specific hardware to complete a task. The system uses QR code which is basically a two-dimensional black and white image encoding a piece of digital information. When a user logs into a site, the web server will generate a challenge encoded to form a QR code. The user captures a picture of QR code with a mobile camera which results in decoding the QR code. The challenge shall be sent back to the server; the web server then logs the PC browser in. The authentication using Challenge-Response is easy to understand and the process is fast. The system proposes the improvement of usability and security of online authentication.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.330-339
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• 2012

In this paper, we define and design the Streaming as a Service (StraaS) to support streaming service based on cloud computing. And we describe the various function and security to StraaS service. Specially, we introduce KS-MMA(Key-generation System for Multilateral Matching Authentication) and SIES(Searchable Image Encryption System) as security function for streaming service and cloud computing.