• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.217-228
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• 2019

In the 4th Industrial Revolution, the Internet of Things emerged and various services and convenience improved. As the frequency of use increases, security threats such as leakage of personal information coexist and the importance of security are increasing. In this paper, we analyze the security threats of the Internet of things and propose a model for enhancing security through user authentication using Fast IDentity Online (FIDO). As a result, we propose to implement strong user authentication by introducing second authentication through FIDO.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.21-27
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• 2019

The video compression standard required a processing technique for a high resoluion image and increased the coding size to increase the resolution of the image. Accurate motion estimation and increased coding size provide high accuracy and compression rate, but there is a problem of increased computational complexity. In this paper, we use DCT - based motion estimation in the frequency domain to reduce complexity. However, we found that the DCT and quantization process used in a general video encoder are applied to the frequency domain encoder, resulting in problems caused by the scaling process. Therfore, in this paper, we extract the scaling matrix that can be applied in the DCT step and resolve the, and improve the performance of motion estimation using increased coding size.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.892-911
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• 2019

Biometric recognition systems have been widely used for information security. Among the most popular biometric traits, there are fingerprint and face due to their high recognition accuracies. However, the security system that uses face recognition as the login method are vulnerable to face-spoofing attacks, from using printed photo or video of the valid user. In this study, we propose a fast and robust method to detect face-spoofing attacks based on the analysis of spatial frequency differences between the real and fake videos. We found that the effect of a spoofing attack stands out more prominently in certain regions of the 2D Fourier spectra and, therefore, it is adequate to use the information about those regions to classify the input video or image as real or fake. We adopt a divide-conquer-aggregate approach, where we first divide the frequency domain image into local blocks, classify each local block independently, and then aggregate all the classification results by the weighted-sum approach. The effectiveness of the methodology is demonstrated using two different publicly available databases, namely: 1) Replay Attack Database and 2) CASIA-Face Anti-Spoofing Database. Experimental results show that the proposed method provides state-of-the-art performance by processing fewer frames of each video.

• Korean Parent-Child Health Journal
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• v.8 no.2
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• pp.112-122
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• 2005

Purpose: This study was done to investigate the relation to perceived maternal child rearing behaviors and the level of internet addiction in the upper year grade students. Method: Data was collected through self-report questionnaires in which perceived maternal child rearing behaviors and internet addiction. This study population was comprised of 668 students who enrolled 4~6 year-grade in Kwangwon-Do. The data collected was analyzed by the SPSS program. Results: The level of internet addiction of subjects was rather low. Of the children, 88.2% reported being average on-line users, 7.3%, heavy on-line users, and 4.5%, internet addicted. Gender, existence of father, mother's attitude when child overuse on-line, average playing time of on-line per day, frequency of on-line visits per week and purpose of on-line use for average on-line users were different from that of heavy on-line users. The level of perceived maternal child rearing behaviors were abbreviate positively correlated to the level of internet addiction in subjects. Conclusion: We suggest these results be used to develop a internet addiction prevention program.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2153-2169
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• 2012

Femtocells provide high quality indoor communications with low transmit power. However, when femtocells are applied in cellular systems, a co-channel interference problem between macrocells and femtocells occurs because femtocells use the same spectrum as do the macrocells. To solve the co-channel interference problem, a previous study suggested a resource allocation scheme in LTE cellular systems using FFR. However, this conventional resource allocation scheme still has interference problems between macrocells and femtocells near the boundary of the sub-areas. In this paper, we define an optimization problem for resource allocation to femtocells and propose a femtocell resource allocation scheme to solve the optimization problem and the interference problems of the conventional scheme. The evaluation of the proposed scheme is conducted by System Level Simulation while varying the simulation environments. The simulation results show that the proposed scheme is superior to the conventional scheme and that it improves the overall performance of cellular systems.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.206-212
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• 2020

The purpose of this study is to analyze the structural relationship among information attitude, brand attitude, usage satisfaction, brand image and brand loyalty of YouTube sports Contents. The survey subjects to achieve the purpose of this study were selected the 490 YouTube sports contents Viewer in the metropolitan area. Data processing was done with SPSS 23 for frequency analysis, Cronbach's α analysis. Also, AMOS 21 was used for confirmatory factor analysis and structural equation model analysis. The results of the analysis are as follows: First, it is more effective to increase the attitude toward the brand itself rather than information attitude to use satisfaction Second, both information attitude and brand attitude were found to have a positive effect on enhancing brand image. In relation to attitude and image, it was possible to achieve research accumulation for YouTube users. Third, it was found that both the use satisfaction and the brand image presented in the previous study had a positive effect on brand loyalty.

• MALSORI
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• no.63
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• pp.139-151
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• 2007

As the Internet becomes prevalent in our lives, harmful contents, such as phornographic videos, have been increasing on the Internet, which has become a very serious problem. To prevent such an event, there are many filtering systems mainly based on the keyword-or image-based methods. The main purpose of this paper is to devise a system that classifies pornographic videos based on the audio information. We use the mel-cepstrum modulation energy (MCME) which is a modulation energy calculated on the time trajectory of the mel-frequency cepstral coefficients (MFCC) as well as the MFCC as the feature vector. For the classifier, we use the well-known Gaussian mixture model (GMM). The experimental results showed that the proposed system effectively classified 98.3% of pornographic data and 99.8% of non-pornographic data. We expect the proposed method can be applied to the more accurate classification system which uses both video and audio information.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.8
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• pp.913-923
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• 2003

This study divides consumers into groups according to the TRI(technology readiness index) in order to (md out the characteristics of each consumer group, and attempts to examine how the frequency of shopping and the TRI affect service quality of and satisfaction at the internet apparel shopping sites. An on-line survey was made to collect data, and the replies from 785 people, who had an experience of apparel shopping apparel on line, were used in the analysis. The research results are as follows: 1. The four factors of optimism, innovativeness, discomfort, and insecurity were identified from the TRI factor analysis, and the total variance was 58.88%. 2. The male group showed the higher TRI than the female group. Especially the factor of innovativeness was higher in the male group, indicating the male group's activeness in the use of technology. 3. Consumers were classified into five types in terms of the TRI: explorers, pioneers, skeptics, paranoids, and laggards. 4. Service quality had the greatest influence on consumers’satisfaction with the apparel shopping sites, and the frequency of purchase, optimism, and discomfort ranked next to service quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2188-2203
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• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.

• Nutrition Research and Practice
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• v.4 no.1
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• pp.51-57
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• 2010

We performed this study to examine lifestyle patterns and dietary behavior based on the level of Internet addiction of Korean adolescents. Data were collected from 853 Korean junior high school students. The level of Internet addiction was determined based on the Korean Internet addiction self-scale short form for youth, and students were classified as high-risk Internet users, potential-risk Internet users, and no risk Internet users. The associations between the students' levels of Internet addiction and lifestyle patterns and dietary behavior were analyzed using a chi-square test. Irregular bedtimes and the use of alcohol and tobacco were higher in high-risk Internet users than no risk Internet users. Moreover, in high-risk Internet users, irregular dietary behavior due to the loss of appetite, a high frequency of skipping meals, and snacking might cause imbalances in nutritional intake. Diet quality in high-risk Internet users was also worse than in potential-risk Internet users and no risk Internet users. We demonstrated in this study that high-risk Internet users have inappropriate dietary behavior and poor diet quality, which could result in stunted growth and development. Therefore, nutrition education targeting high-risk Internet users should be conducted to ensure proper growth and development.