• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.425-431
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• 2017

As drones gain more popularity these days, drone detection becomes more important part of the drone systems for safety, privacy, crime prevention and etc. However, existing drone detection systems are expensive and heavy so that they are only suitable for industrial or military purpose. This paper proposes a novel approach for training Convolutional Neural Networks to detect drones from images that can be used in embedded systems. Unlike previous works that consider the class probability of the image areas where the class object exists, the proposed approach takes account of all areas in the image for robust classification and object detection. Moreover, a novel loss function is proposed for the CNN to learn more effectively from limited amount of training data. The experimental results with various drone images show that the proposed approach performs efficiently in real drone detection scenarios.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.111-116
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• 2019

The digital forensic analysis ensures the integrity of confiscated data by calculating hash values for seizure and search of digital evidence and receiving confirmation and signature from participants. However, evidence that is irrelevant to the alleged offense needs to be deleted even after seizure from the point of view of privacy. But the hash value is altered by deleting the irrelevant data from the image file, one will not be able to prove that the file is in the initial state when it was seized. Therefore, in this paper, a study was conducted to support the integrity of the digital evidence, even if some of the seized digital evidence was deleted or damaged during the seizure search. The hash value of each data is calculated and hash value of the combination of hash values are also calculated. Even if the unrelated evidence is deleted from the seized evidence regardless of file system such as FAT or NTFS, the suggested method presented a way to provide the integrity that proves there is no change in the evidence file.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.204-210
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• 2019

Mobile Crowd Computing is one of the most efficient and effective way to collect the Electronic health records and they are very intelligent in processing them. Mobile Crowd Computing can handle, analyze and process the huge volumes of Electronic Health Records (EHR) from the high-performance Cloud Environment. Electronic Health Records are very sensitive, so they need to be secured, authenticated and processed efficiently. However, security, privacy and authentication of Electronic health records(EHR) and Patient health records(PHR) in the Mobile Crowd Computing Environment have become a critical issue that restricts many healthcare services from using Crowd Computing services .Our proposed Efficient Multi-layer Encryption Framework(MLEF) applies a set of multiple security Algorithms to provide access control over integrity, confidentiality, privacy and authentication with cost efficient to the Electronic health records(HER)and Patient health records(PHR). Our system provides the efficient way to create an environment that is capable of capturing, storing, searching, sharing, analyzing and authenticating electronic healthcare records efficiently to provide right intervention to the right patient at the right time in the Mobile Crowd Computing Environment.

• The Korean Journal of Franchise Management
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• v.12 no.4
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• pp.25-40
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• 2021

Purpose: Marketing communication with customers is essential for companies to survive and grow in a fiercely competitive environment. Advertising is one of the most readily accepted marketing communications by consumers. Unlike a company that owns a distribution network, advertising is vital for a franchise. In general, many advertising models select celebrities. Celebrities are more likely to attract audience attention and influence consumers' purchase intentions. Customers satisfied with advertising are more likely to stay loyal and buy again when the company launches a new product. In addition, customers form a brand image through advertisements. Therefore, in this study, the effect of the characteristics of the foodservice franchise advertising model characteristics on model satisfaction, brand image, and purchase intention. Research design, data, and methodology: The survey of this study was conducted among consumers over the age of 20 who had seen a restaurant franchise advertisement and visited a store within the last 2 months. 305 copies were collected for 7 days during the survey period, from October 21 to October 27, 2021. Among the collected questionnaires, 12 insincere questionnaires were excluded, and 293 were used for analysis. SPSS 25.0 and Smart PLS 3.0 were used as data collected to test the hypothesis. Result: As a result of the study, among the advertising model characteristics of a foodservice franchise, reliability, attractiveness, expertise, and closeness all had a significant positive (+) effect on model satisfaction. In addition, reliability and closeness were found to have a significantly positive (+) effect on brand satisfaction, but attractive and expertise did not significantly affect brand image. Finally, model satisfaction was found to have a significant positive (+) effect on brand image and purchase intention. Brand image also appeared to have a significant positive effect on purchase intention. Conclusions: Research Results First, this study verified the effect of a restaurant franchise advertising model using celebrities by using the characteristics of the advertising model. Second, this study developed a conceptual structure for model characteristics - model satisfaction - brand image - purchase intention. Third, the restaurant franchise marketer needs to select a model in consideration of the privacy of the advertising model. Fourth, consumers tend to equate advertising models with advertising

• Journal of KIISE
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• v.42 no.2
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• pp.162-168
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• 2015

Image data is mostly stored in compressed form because of its huge size. Therefore, a series of cumbersome procedures is required to apply a transformation to image data: decompression, extraction of spatial data, transformation and recompression. In this paper, we employ DCT(Discrete Cosine Transform) coefficients to change the spatial presentation of images. DCT is commonly used in still image compression standards such as JPEG and moving picture compression standards such as MPEG-2, MPEG-4, and H.264. In this paper, we derived mathematically the relationship between the geometry transformation in the spatial domain and coefficient changes in the DCT domain and verified it with images in the JPEG file format. Because of the efficiency of transformation in the frequency domain, our findings can be utilized for light-weight partial image encryption for privacy data protection or entertainment contents protection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.859-866
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• 2019

Cybersecurity attack targeting a specific user is rising in number, even enterprises are trying to strengthen their cybersecurity. Network segmentation environment where public network and private network are separated could block information coming from the outside, however, it is unable to control outside information for business efficiency and productivity. Even if enterprises try to enhance security policies and introduce the network segmentation system and a solution incorporating CDR technology to remove unnecessary data contained in files, it is still exposed to security threats. Therefore, we suggest a system that uses file format conversion to transmit a secure file in the network separation environment. The secure file is converted into an image file from a document, as it reflects attack patterns of inserting malicious code into the document file. Additionally, this paper proposes a system in the environment which functions that a document file can keep information for incident response, considering forensic readiness.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.81-87
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• 2012

The current defacing method for keeping an anonymity of brain images damages the integrity of a precise brain analysis due to over removal, although it maintains the patients' privacy. A novel method has been developed to create an anonymous face model while keeping the voxel values of an image exactly the same as that of the original one. The method contains two steps: construction of a mockup brain template from ten normalized brain images and a substitution of the mockup brain to the brain image. A level set segmentation algorithm is applied to segment a scalp-skull apart from the whole brain volume. The segmented mockup brain is coregistered and normalized to the subject brain image to create an anonymous face model. The validity of this modification is tested through comparing the intensity of voxels inside a brain area from the mockup brain with the original brain image. The result shows that the intensity of voxels inside from the mockup brain is same as ones from an original brain image, while its anonymity is guaranteed.

• The Journal of the Korea institute of electronic communication sciences
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• v.3 no.4
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• pp.295-303
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• 2008

Under the obligations which is a protection of privacy and a respect for human rights of each person critical is caused by time about surveillance system and CCTV markets which stagnate during that about 911 terror after that securities about importance raising and direction of a ceremony crime prevention are caused by with world grafting of up-to-date IT technique of domestic and changes with the intelligent style surveillance system which leads and quite from the remote place the dead zone this the image which is photographed the Internet leads and with the intelligent style CCTV surveillance systems will be able to control which area at real-time watch and is embodied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.11
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• pp.994-999
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• 2014

Nowadays we use biometrics such as face, fingerprint or palm print for registration and authentication with smart phone. When use camera function of smart phone, normally they overlay a specific image on camera preview as guideline and induce user to take picture uniformly. In this paper, use palm print for authentication factor with smart phone, we propose a new guideline and show the result about user experiment in terms of authentication success ratio.

• International Journal of Contents
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• v.9 no.2
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• pp.14-21
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• 2013

Current smartphone authentication systems are deemed inconvenient and difficult for users on remembering their password as well as privacy issues on stolen or forged biometrics. New authentication system is demanded to be implicit to users with very minimum user involvement being. This idea aims towards a future model of authentication system for smartphones users without users realizing them being authenticated. We use the most frequent activity that users carry out with their smartphone, which is the calling activity. We derive two basics related interactions that are first factor being arm's flex (AF) action to pick a phone to be near ones' ears and then once getting near ear using second factor from ear shape image. Here, we combine behavior biometrics from AF in first factor and physical biometrics from ear image in second factor. Our study shows our dual-factor authentication system does not require explicit user interaction thereby improving convenience and alleviating burden from users from persistent necessity to remember password. These findings will augment development of novel implicit authentication system being transparent, easier, and unobtrusive for users.