• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.115-122
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• 2019

CCTV(Closed-Circuit Television) is increasingly exposed to CCTV per person as the number of installations increases every year for accident prevention and facility safety. The intelligent video surveillance system technology is attracting attention to the privacy protection of exposed subjects. The intelligent video surveillance system performs a process for the privacy protection so as to perform the action type of the subject and the judgment of the situation in the simple identification of the photographed image data, or to prevent the information, from which the information of the photographed subject is exposed. The proposed technique is applied to the video surveillance system and converts the original image information taken from the video surveillance system into similar image information so that the original image information is not leaked to the outside. In this paper, we propose an image conversion mechanism that inserts a virtual face image that approximates a preset similarity.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.49-55
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• 2008

The face extraction is very important to provide the images of the roads and road sides without the problem of privacy. For face extraction form roadside images, we detected the skin color area by using HSI and YCrCb color models. Efficient skin color detection was achieved by using these two models. We used a connectivity and intensity difference for grouping, skin color regions further we applied shape conditions (rate, area, number and oval condition) and determined face candidate regions. We applied thresholds to region, and determined the region as the face if black part was over 5% of the whole regions. As the result of the experiment 28 faces has been extracted among 38 faces had problem of privacy. The reasons which the face was not extracted were the effect of shadow of the face, and the background objects. Also objects with the color similar to the face were falsely extracted. For improvement, we need to adjust the threshold.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.640-654
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• 2021

Purpose: Normal education operation was difficult in the national disaster situation of Coronavirus Infection-19. Non-face-to-face education can be an alternative to face to face education, but it is not easy to provide the same level of education. In this study, the professor of disaster management field will identify problems that can occur in the overall operation and progress of non-face-to-face education and seek ways to improve non-face-to-face education. Method: Non-face-to-face real-time education was largely categorized into pre-class, in-class, post-class, and evaluation, and case studies were conducted through the professor's case studies. Result&Conclusion: The results of the survey are as follows: First, pre-class, it was worth considering providing a non-face-to-face educational place for professors, and the need for prior education on non-face-to-face educational equipment and systems was required. In addition, it seems necessary to make sure that education is operated smoothly by giving enough notice on classes and to make efforts to develop non-face-to-face education programs for practical class. Second, communication between professor and learner, and among learners can be an important factor in non-face-to-face mid classes. To this end, it is necessary to actively utilize debate-type classes to lead learners to participate in education and enhance the educational effect through constant interaction. Third, non-face-to-face post classes, policies on the protection of privacy due to video records should be prepared to protect the privacy of professors in advance, and copyright infringement on educational materials should also be considered. In addition, it is necessary to devise various methods for fair and objective evaluation. According to the results of the interview, in the contents, which are components of non-face-to-face education, non-face-to-face education requires detailed plans on the number of students, contents, and curriculum suitable for non-face-to-face education from the design of the education. In the system, it is necessary to give the professor enough time to fully learn and familiarize with the function of the program through pre-education on the program before the professor gives non-face-to-face classes, and to operate the helpdesk, which can thoroughly check the pre-examination before non-face-to-face education and quickly resolve the problem in case of a problem.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.97-106
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• 2014

CCTV(Closed Circuit television) is one of the widely used physical security technologies and video acquisition device installed at specific point with various purposes. Recently, as the CCTV capabilities improve, facial recognition from the information collected from CCTV video is under development. However, in case these technologies are exploited, concerns on major privacy infringement are high. Especially, a computer connected to a particular space images taken by the camera in real time over the Internet has emerged to show information services. In the privacy law, safety measures which is related with biometric template are notified. Accordingly, in this paper, for the protection of privacy video information in the video surveillance system, the technical and managerial requirements for video information security are suggested.

• Current Optics and Photonics
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• v.4 no.5
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• pp.421-427
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• 2020

A novel privacy-protection device to prevent visual hacking is realized by using a directional backlight and facial recognition. The proposed method is able to overcome the limitations of previous privacy-protection methods that simply restrict the viewing angle to a narrow range. The accuracy of user tracking is accomplished by the combination of a time-of-flight sensor and facial recognition with no restriction of detection range. In addition, an experimental demonstration is provided to verify the proposed scheme.

• Electronics and Telecommunications Trends
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• v.36 no.4
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• pp.135-144
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• 2021

The field of user authentication in Korea has experienced new dimensions since December 2020. Accredited certificate, which had been in use for 21 years since 1999, has been abolished. Accredited certificates have provided a trust foundation for various ICT-based industrial developments; however, new changes in the authentication sector are also required due to changes in the service and policy environment. Changes in the service environment occur rapidly because of the emergence of new technologies such as AI, IoT, Bio, Blockchain, and the daily use of non-face-to-face environments caused by COVID-19. Even with changes in the service environment, user authentication remains an essential foundation for providing services. This paper summarizes the current status of user authentication techniques, analyzes major changes in the service environment (such as Metaverse) associated with user authentication, and presents the direction of authentication techniques (Decentralized, Invisible, Privacy-preserving) through the derived implications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2827-2848
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• 2021

Mobile Crowdsourcing (MCS) has become an emerging paradigm evolved from crowdsourcing by employing advanced features of mobile devices such as smartphones to perform more complicated, especially spatial tasks. One of the key procedures in MCS is to collect answers from mobile users (workers), which may face several security issues. First, authentication is required to ensure that answers are from authorized workers. In addition, MCS tasks are usually location-dependent, so the collected answers could disclose workers' location privacy, which may discourage workers to participate in the tasks. Finally, the overhead occurred by authentication and privacy protection should be minimized since mobile devices are resource-constrained. Considering all the above concerns, in this paper, we propose a lightweight and privacy-preserving answer collection scheme for MCS. In the proposed scheme, we achieve anonymous authentication based on traceable ring signature, which provides authentication, anonymity, as well as traceability by enabling malicious workers tracing. In order to balance user location privacy and data availability, we propose a new concept named current location privacy, which means the location of the worker cannot be disclosed to anyone until a specified time. Since the leakage of current location will seriously threaten workers' personal safety, causing such as absence or presence disclosure attacks, it is necessary to pay attention to the current location privacy of workers in MCS. We encrypt the collected answers based on timed-release encryption, ensuring the secure transmission and high availability of data, as well as preserving the current location privacy of workers. Finally, we analyze the security and performance of the proposed scheme. The experimental results show that the computation costs of a worker depend on the number of ring signature members, which indicates the flexibility for a worker to choose an appropriate size of the group under considerations of privacy and efficiency.

• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1156-1162
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• 2013

Face verification has been widely studied during the past two decades. One of the challenges is the rising concern about the security and privacy of the template database. In this paper, we propose a secure face verification system which generates a unique secure cryptographic key from a face template. The face images are processed to produce face templates or codes to be utilized for the encryption and decryption tasks. The result identity data is encrypted using Advanced Encryption Standard (AES). Distance metric naming hamming distance and Euclidean distance are used for template matching identification process, where template matching is a process used in pattern recognition. The proposed system is tested on the ORL, YALEs, and PKNU face databases, which contain 360, 135, and 54 training images respectively. We employ Principle Component Analysis (PCA) to determine the most discriminating features among face images. The experimental results showed that the proposed distance measure was one the promising best measures with respect to different characteristics of the biometric systems. Using the proposed method we needed to extract fewer images in order to achieve 100% cumulative recognition than using any other tested distance measure.

• Journal of the Semiconductor & Display Technology
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• v.6 no.2 s.19
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• pp.59-63
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• 2007

Radio Frequency Identification (RFID) is a common term for technologies using micro chips that are able to communicate over short-range radio and that can be used for identifying physical objects. RFID technology already has several application areas and more are being envisioned all the time. While it has the potential of becoming a really ubiquitous part of the information society over time, there are many security and privacy concerns related to RFID that need to be solved. This paper proposes a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. This method improved linear discriminant analysis has reduced the dimension of feature information which has large size of data. Therefore, face feature information can be stored in small memory field of RFID tag. The proposed algorithm in comparison with other previous methods shows better stability and elevated detection rate and also can be applied to the entrance control management system, digital identification card and others.