• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.21-28
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• 2009

In the recent years, power attacks were widely investigated, and so various countermeasures have been proposed, In the case of block ciphers, masking methods that blind the intermediate values in the algorithm computations(encryption, decryption, and key-schedule) are well-known among these countermeasures. But the cost of non-linear part is extremely high in the masking method of block cipher, and so the inversion of S-box is the most significant part in the case of AES. This fact make various countermeasures be proposed for reducing the cost of masking inversion and Zakeri's method using normal bases over the composite field is known to be most efficient algorithm among these masking method. We rearrange the masking inversion operation over the composite field and so can find duplicated multiplications. Because of these duplicated multiplications, our method can reduce about 10.5% gates in comparison with Zakeri's method.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.461-475
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• 2021

Hidden Markov model (HMM) is a statistical model in which the system consists of two elements, hidden states and observable results. HMM has been actively used in various fields, especially for time series data in the financial sector, since it has a variety of mathematical structures. Based on the HMM theory, this research is intended to apply the domestic KOSPI200 stock index as well as the prediction of global stock indexes such as NIKKEI225, HSI, S&P500 and FTSE100. In addition, we would like to compare and examine the differences in results between the HMM and support vector regression (SVR), which is frequently used to predict the stock price, due to recent developments in the artificial intelligence sector.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.331-340
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• 2021

As the communication industry develops, the development of SoC (System on Chip) is increasing. Accordingly, the paradigm of technology design of industries and companies is changing. In the existing process, companies purchased micro-architecture, but now they purchase ISA (Instruction Set Architecture), and companies design the architecture themselves. RISC-V is an open instruction set based on a reduced instruction set computer. RISC-V is equipped with ISA, which can be expanded through modularization, and an expanded version of ISA is currently being developed through the support of global companies. In this paper, we present benchmarking frameworks ARIA, LEA, and PIPO of Korean block ciphers in RISC-V. We propose implementation methods and discuss performance by utilizing the basic instruction set and features of RISC-V.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.29-38
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• 2021

The social studies, mathematics, and science textbooks of the elementary curriculum will begin to be authorized from 2022. This study explores the effect of textbooks based on a gamification motivation strategy on learner interest. For this purpose, this study analyzes whether the systematic application of the gamification motivation strategy to elementary studies textbooks, which will be authorized from 2022, can develop this textbook into a "learner-centered curriculum book that induces interest." More specifically, this study applied Kumsung Publishing's experimental social studies textbooks in class and conducted a questionnaire among 121 third graders to verify the effectiveness of the textbooks. The results show that studies textbooks based on a gamification motivation strategy greatly influence increased learner interest in the classroom. The textbooks also represent a positive influence in learner understanding, interest, and curiosity regarding the class content and assistance. Demonstrating that gamification motivation strategy is worthwhile to actively apply in future textbook development for the enhancement of learners' interests, this study is significant in that it has presented a meaningful textbook development model.

• Journal of Internet of Things and Convergence
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• v.7 no.1
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• pp.9-19
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• 2021

The data mining design incorporated with big data based cloud computing system is investigated for the nuclear terrorism prevention where the conventional physical protection system (PPS) is modified. The networking of terror related bodies is modeled by simulation study for nuclear forensic incidents. It is needed for the government to detect the terrorism and any attempts to attack to innocent people without illegal tapping. Although the mathematical algorithm of the study can't give the exact result of the terror incident, the potential possibility could be obtained by the simulations. The result shows the shape oscillation by time. In addition, the integration of the frequency of each value can show the degree of the transitions of the results. The value increases to -2.61741 in 63.125th hour. So, the terror possibility is highest in later time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1263-1270
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• 2020

The differential fault attacks (DFA) are cryptoanalysis methods that reveal the secret key utilizing differences between the normal and faulty ciphertexts, which occurred when artificial faults are injected into an encryption device. The conventional DFA methods use faults to falsify intermediate values. Meanwhile, we propose the novel DFA method that uses a fault to skip a function. The proposed method has a very low attack complexity that reveals the secret key using one fault injected ciphertext within seconds. Also, we proposed a method that filters out ciphertexts where the injected faults did not occur the function-skipping. It makes our method realistic. To demonstrate the proposed method, we performed fault injection on the Riscure's Piñata board. As a result, the proposed method can filter out and reveal the secret key within seconds on a real device.

• Journal of IKEEE
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• v.24 no.4
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• pp.954-960
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• 2020

This paper proposes a speed variable proportional resonant current control method for a single-phase permanent magnet synchronous motor(PMSM). Due to the electromagnetic characteristics of a single-phase PMSM, negative and zero torques are generated in the part corresponding to the phase difference between the stator current and the back electromotive force. In addition, overcurrent limitation is required because of the low stator resistance and inductance in sensorless operation. When using the vector control for current control of single-phase PMSM under these conditions, processes of coordinate transformation, inverse coordinate transformation, and generation of virtual dq-axis components are required. However, the proposed variable speed proportional resonant current control method does not need the coordinate transformation used for AC motors. In this paper, we have confirmed stable maneuverability by using variable proportional resonant current control algorithm, and proposed sensorless control based on a mathematical model of a single-phase PMSM without a position sensor when reaching a constant speed. The usefulness of the current control method was verified through several experiments.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.49-57
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• 2020

In this paper, I provided an approximation function Li*2,10(x) using logarithm integral for the counting function π*2,10(x) of consecutive deca primes. Several personal computers and Mathematica were used to validate the approximation function Li*2,10(x). I found the real value of π*2,10(x) and approximate value of Li*2,10(x) for various x ≤ 1011. By the result of theses calculations, most of the error rates are margins of error of 0.005%. Also, I proved that the sum C2,10(∞) of reciprocals of all primes with difference 10 between primes is finite. To find C2,10(∞), I computed the sum C2,10(x) of reciprocals of all consecutive deca primes for various x ≤ 1011 and I estimate that C2,10(∞) probably lies in the range C2,10(∞)=0.4176±2.1×10-3.

• Smart Media Journal
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• v.10 no.1
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• pp.55-62
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• 2021

We applied machine learning of semi-supervised learning, transfer learning, and federated learning as examples of AI use cases that can be applied to the three major industries(Automobile industry, Energy industry, and AI/Healthcare industry) of Gwangju Metro-city, and established an ML strategy for AI services for the major industries. Based on the ML strategy of AI service, practical approaches are suggested, the semi-supervised learning approach is used for automobile image recognition technology, and the transfer learning approach is used for diabetic retinopathy detection in the healthcare field. Finally, the case of the federated learning approach is to be used to predict electricity demand. These approaches were tested based on hardware such as single board computer Raspberry Pi, Jaetson Nano, and Intel i-7, and the validity of practical approaches was verified.

• Smart Media Journal
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• v.10 no.1
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• pp.99-107
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• 2021

In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.