• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.23-35
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• 2009

Password-Authenticated Key Exchange (PAKE) Protocol is a useful tool for secure communication conducted over open networks without sharing a common secret key or assuming the existence of the public key infrastructure (PKI). It seems difficult to design efficient PAKE protocols using RSA, and thus many PAKE protocols are designed based on the Diffie-Hellman key exchange (DH-PAKE). Therefore it is important to design an efficient PAKE based on RSA function since the function is suitable for designing a PAKE protocol for imbalanced communication environment. In this paper, we propose a computationally-efficient key exchange protocol based on the RSA function that is suitable for low-power devices in imbalanced environment. Our protocol is more efficient than previous RSA-PAKE protocols, required theoretical computation and experiment time in the same environment. Our protocol can provide that it is more 84% efficiency key exchange than secure and the most efficient RSA-PAKE protocol CEPEK. We can improve the performance of our protocol by computing some costly operations in offline step. We prove the security of our protocol under firmly formalized security model in the random oracle model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.135-141
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• 2011

Recent advances in mobile devices and development of various mobile applications dealing with private information of users made user authentication in mobile devices a very important issue. This paper presents a new user authentication method based on touch screen interfaces. This method uses for authentication the PIN digits as well as the exact locations the user touches to input these digits. Our method is fully compatible with the regular PIN entry method which uses numeric keypads, and it provides better usability than the behavioral biometric schemes because its PIN registration process is much simpler. According to our experiments, our method guarantees EERs of 12.8%, 8.3%, and 9.3% for 4-digit PINs, 6-digit PINs, and 11-digit cell phone numbers, respectively, under the extremely conservative assumption that all users have the same PIN digits and cell phone numbers. Thus we can guarantee much higher performance in identification functionality by applying this result to a more practical situation where every user uses distinct PIN and sell phone number. Finally, our method is far more secure than the regular PIN entry method, which is verified by our experiments where attackers are required to recover a PIN after observing the PIN entry processes of the regular PIN and our method under the same level of security parameters.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.58-73
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• 2020

The purpose of this study is to empirically analyze the relationship between organizational commitment, job satisfaction, education and training, human resource development, and communication in Korea's financial industry. In particular, the mediating relationships between organizational commitment and job satisfaction, education and training, human resource development, and communication were examined in order to provide a better understanding of organizational commitment. A structural equation model was used for the empirical analysis of this study. As a result of the study, it was confirmed that education and training, human resource development, communication, organizational commitment, and job satisfaction are correlated within the Korean financial industry. Furthermore, organizational commitment was found to have mediating effects on education and training, human resource development, communication, and job satisfaction. Based on these results, this study emphasizes the importance of education and training for organizational commitment in the Korean financial industry. In particular, this study establishes the importance of a culture of trust within organizations through human resource development programs, communication for job satisfaction, and organizational performance to face changes in the post-COVID era. In the future, more in-depth qualitative studies are required to derive factors related to the employees of financial companies and to conduct comparison analyses with companies in other industries.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.541-551
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• 2021

Among the numerous duties of a librarian in a library, the work of arranging books is a job that the librarian has to do one by one. Thus, the cost of labor and time is large. In order to solve this problem, the interest in book-arranging robots based on artificial intelligence has recently increased. In this paper, we propose the K-ACO algorithm, which is the shortest path algorithm for multi-stops that can be applied to the library book arrangement robots. The proposed K-ACO algorithm assumes multiple robots rather than one robot. In addition, the K-ACO improves the ANT algorithm to create K clusters and provides the shortest path for each cluster. In this paper, the performance analysis of the proposed algorithm was carried out from the perspective of book arrangement time. The proposed algorithm, the K-ACO algorithm, was applied to a university library and compared with the current book arrangement algorithm. Through the simulation, we found that the proposed algorithm can allocate fairly, without biasing the work of arranging books, and ultimately significantly reduce the time to complete the entire work. Through the results of this study, we expect to improve quality services in the library by reducing the labor and time costs required for arranging books.

• Knowledge Management Research
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• v.22 no.2
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• pp.247-268
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• 2021

Investors mainly use PER and PBR among financial ratios for valuation and investment decision-making. I conduct an analysis of two basic financial ratios from a statistical perspective. Financial ratios contain key accounting numbers which reflect firm fundamentals and are useful for valuation or risk analysis such as enterprise credit evaluation and default prediction. The distribution of financial data tends to be extremely heavy-tailed, and PER and PBR show exceedingly high level of kurtosis and their extreme cases often contain significant information on financial risk. In this respect, Extreme Value Theory is required to fit its right tail more precisely. I introduce not only GPD but exGPD. GPD is conventionally preferred model in Extreme Value Theory and exGPD is log-transformed distribution of GPD. exGPD has recently proposed as an alternative of GPD(Lee and Kim, 2019). First, I conduct a simulation for comparing performances of the two distributions using the goodness of fit measures and the estimation of 90-99% percentiles. I also conduct an empirical analysis of Information Technology firms in Korea. Finally, exGPD shows better performance especially for PBR, suggesting that exGPD could be an alternative for GPD for the analysis of financial ratios.

• Geophysics and Geophysical Exploration
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• v.24 no.2
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• pp.53-66
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• 2021

Velocity model building is an essential procedure in seismic data processing. Conventional techniques, such as traveltime tomography or velocity analysis take longer computational time to predict a single velocity model and the quality of the inversion results is highly dependent on human expertise. Full-waveform inversions also depend on an accurate initial model. Recently, deep neural network techniques are gaining widespread acceptance due to an increase in their integration to solving complex and nonlinear problems. This study investigated cases of seismic velocity model building using deep neural network techniques by classifying items according to the neural networks used in each study. We also included cases of generating training synthetic velocity models. Deep neural networks automatically optimize model parameters by training neural networks from large amounts of data. Thus, less human interaction is involved in the quality of the inversion results compared to that of conventional techniques and the computational cost of predicting a single velocity model after training is negligible. Additionally, unlike full-waveform inversions, the initial velocity model is not required. Several studies have demonstrated that deep neural network techniques achieve outstanding performance not only in computational cost but also in inversion results. Based on the research results, we analyzed and discussed the characteristics of deep neural network techniques for building velocity models.

• Journal of IKEEE
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• v.25 no.2
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• pp.273-279
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• 2021

In this paper, we propose an algorithm that shortens the learning time by performing individual learning using partitioning the deep learning structure. The proposed algorithm consists of four processes: network classification origin setting process, feature vector extraction process, feature noise removal process, and class classification process. First, in the process of setting the network classification starting point, the division starting point of the network structure for effective feature vector extraction is set. Second, in the feature vector extraction process, feature vectors are extracted without additional learning using the weights previously learned. Third, in the feature noise removal process, the extracted feature vector is received and the output value of each class is learned to remove noise from the data. Fourth, in the class classification process, the noise-removed feature vector is input to the multi-layer perceptron structure, and the result is output and learned. To evaluate the performance of the proposed algorithm, we experimented with the Extended Yale B face database. As a result of the experiment, in the case of the time required for one-time learning, the proposed algorithm reduced 40.7% based on the existing algorithm. In addition, the number of learning up to the target recognition rate was shortened compared with the existing algorithm. Through the experimental results, it was confirmed that the one-time learning time and the total learning time were reduced and improved over the existing algorithm.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.10-16
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• 2020

Deterioration of reinforced concrete structure caused by chloride ingress is the main issue and regrading this, many studies have been investigated with both experiments and computational modelling. In addition to chloride diffusion, chloride sorption should be considered as a chloride transport mechanism in concrete structure and cracks formed in concrete structures are the main variable to evaluate the performance of the structures. In this study, after making two types of cracks width (0.1 and 0.3 mm) in reinforced concretes, chloride absorption tests were performed. Weight change and colour change using 0.1 AgNO3 solution from the samples were performed to measure chloride ingress. Image processing was also carried out to quantify range of colour change in carck face. From the result, it were confirmed that the amount of chloride absorption increases with exposure time and increasing crack width, and chlorides reached at steel depth within 1 hour. It would be possible that chloride can move through interface bewteen steel and concrete, thereby further study regarding this is required.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.369-377
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• 2021

Augmented reality smart-glass enables healthcare providers to use patient and their care related information without interference of workflow. In addition, augmented reality smart-glass simulation had advantages in improving competency via remote collaboration and real-time information sharing. This study investigated perception and attitude regarding augmented reality smart glass based healthcare simulation on three different groups of healthcare major students, computer major students, developers and faculties. Using convenience sampling method, data were obtained from 95 participants and statistical analysis were performed using SPSS 25.0. Developer and faculty group showed the highest scores, followed by healthcare major students. There was the high expectation on augmented reality smart-glass for skill acquisition and the high performance and big screen were essential features of device. The findings of this study revealed that differences between healthcare and computer major students exist and strategies to reduce those gaps are required to adopt augmented reality smart glass in healthcare settings.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.505-517
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• 2021

Lots of studies have been conducted on work-life balance in various fields. In particular, while a plethora of studies on the work-life balance have focused mainly on organizational culture and work performance, research to investigate the impact of work-life balance on employees' organizational commitment is scarce. This study aims to empirically analyze how work-life balance of employees affects organizational commitment and mediation effects of job satisfaction on the relationships through a survey of 463 employees working in small and medium-sized enterprises, public institutions, and conglomerates in the COVID-19 era. Also, it examines the impact of a smart work environment as a new way of working during the COVID-19 pandemic on job satisfaction and organizational commitment. The findings of the study are summarized as follows. First, work-life balance was shown to positively affect job satisfaction, and job satisfaction had a positive influence on emotional organizational commitment of employees. Second, job satisfaction was found to be completely mediated both in the relationship between work-life balance and organizational commitment and in the relationship between work-family balance and organizational commitment, and partially mediated in the relationship between work-growth balance and organizational commitment. Third, the smart work environment had a positive effect on job satisfaction and organizational commitment. The results of the study show that work and family, work and leisure, and work and growth balance are significantly important factors to improve employees' work attitudes in the changing work environment as a result of COVID-19. The present results suggest that the introduction of work-life balance and the smart work environment is required to increase organizational productivity.