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The Blockchain based Undeniable Multi-Signature Scheme for Protection of Multiple Authorship on Wisdom Contents (지혜콘텐츠 공동저작권 보호에 적합한 블록체인 기반 부인봉쇄 다중서명 기법)

  • Yun, Sunghyun
    • Journal of Internet of Things and Convergence
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    • v.7 no.2
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    • pp.7-12
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    • 2021
  • Wisdom Contents are created with experiences and ideas of multiple authors, and consumed in Internet based Social Network Services that are not subjected to regional restrictions. Existing copyright management systems are designed for the protection of professional authors' rights, and effective in domestic area. On the contrary, the blockchain protocol is subjected to the service and the block is added by the consensus of participating nodes. If the data is stored to the blockchain, it cannot be modified or deleted. In this paper, we propose the blockchain based undeniable multi-signature scheme for the protection of multiple authorship on Wizdom Contents. The proposed scheme is consisted of co-authors' common public key generation, multi-signature generation and verification protocols. In the undeniable signature scheme, the signature cannot be verified without help of the signer. The proposed scheme is best suited to the contents purchase protocol. All co-authors cannot deny the fairness of the automated profit distribution through the verification of multiple authorship on Wizdom Contents.

Effect of dietary supplementation with Allium mongolicum Regel extracts on growth performance, carcass characteristics, and the fat color and flavor-related branched-chain fatty acids concentration in ram lambs

  • Liu, Wangjing;Ao, Changjin
    • Animal Bioscience
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    • v.34 no.7
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    • pp.1134-1145
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    • 2021
  • Objective: This study aimed to investigate the effect of dietary supplementation with Allium mongolicum Regel extracts on the growth performance, carcass characteristics, fat color, and concentrations of three branched-chain fatty acids related to flavor in ram lambs. Methods: Sixty 3-month-old, male, small-tailed Han sheep were selected and randomly allocated into four groups in a randomized block design. Four feeding treatments were used: i) a basal diet without supplementation as the control group (CK); ii) the basal diet supplemented with 10 g/lamb/d Allium mongolicum Regel powder as the AMR group; iii) the basal diet supplemented with 3.4 g/lamb/d Allium mongolicum Regel water extract as the AWE group; and iv) the basal diet supplemented with 2.8 g/lamb/d Allium mongolicum Regel ethanol extract as the AFE group. Results: The results demonstrated that the dry matter intake was lower for the AFE group than that in other groups (p = 0.001). The feed conversion ratio was greater for the AFE than that in other groups (p = 0.039). Dietary supplementation with Allium mongolicum Regel powder and its extracts decreased the concentrations of 4-methyloctanoic acid (MOA) (p<0.001), 4-ethyloctanoic acid (EOA) (p<0.001), and 4-methylnonanoic acid (MNA) (p = 0.044) in perirenal adipose tissue compared to those observed in the CK lambs. Dietary supplementation with Allium mongolicum Regel powder and its extracts decreased the concentrations of MOA (p<0.001) and EOA (p<0.001) in dorsal subcutaneous adipose tissue compared to those in the CK lambs. The concentrations of MOA (p<0.001) and EOA (p = 0.002) in omental adipose tissue were significantly affected by treatment, although there was a tendency for lower MNA (p = 0.062) in AMR, AWE, and AFE lambs than that in CK lambs. Conclusion: This study demonstrated that Allium mongolicum Regel and its extracts could significantly promote feed efficiency, although dry matter intake decreased and could decrease the MOA and EOA concentrations related to characteristic flavor and odor of body fat in lambs, except for tail adipose tissue.

A High-Performance ECC Processor Supporting Multiple Field Sizes over GF(p) (GF(p) 상의 다중 체 크기를 지원하는 고성능 ECC 프로세서)

  • Choe, Jun-Yeong;Shin, Kyung-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.419-426
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    • 2021
  • A high-performance elliptic curve cryptography processor (HP-ECCP) was designed to support five field sizes of 192, 224, 256, 384 and 521 bits over GF(p) defined in NIST FIPS 186-2, and it provides eight modes of arithmetic operations including ECPSM, ECPA, ECPD, MA, MS, MM, MI and MD. In order to make the HP-ECCP resistant to side-channel attacks, a modified left-to-right binary algorithm was used, in which point addition and point doubling operations are uniformly performed regardless of the Hamming weight of private key used for ECPSM. In addition, Karatsuba-Ofman multiplication algorithm (KOMA), Lazy reduction and Nikhilam division algorithms were adopted for designing high-performance modular multiplier that is the core arithmetic block for elliptic curve point operations. The HP-ECCP synthesized using a 180-nm CMOS cell library occupied 620,846 gate equivalents with a clock frequency of 67 MHz, and it was evaluated that an ECPSM with a field size of 256 bits can be computed 2,200 times per second.

Data driven inverse stochastic models for fiber reinforced concrete

  • Kozar, Ivica;Bede, Natalija;Bogdanic, Anton;Mrakovcic, Silvija
    • Coupled systems mechanics
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    • v.10 no.6
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    • pp.509-520
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    • 2021
  • Fiber-reinforced concrete (FRC) is a composite material where small fibers made from steel or polypropylene or similar material are embedded into concrete matrix. In a material model each constituent should be adequately described, especially the interface between the matrix and fibers that is determined with the 'bond-slip' law. 'Bond-slip' law describes relation between the force in a fiber and its displacement. Bond-slip relation is usually obtained from tension laboratory experiments where a fiber is pulled out from a matrix (concrete) block. However, theoretically bond-slip relation could be determined from bending experiments since in bending the fibers in FRC get pulled-out from the concrete matrix. We have performed specially designed laboratory experiments of three-point beam bending with an intention of using experimental data for determination of material parameters. In addition, we have formulated simple layered model for description of the behavior of beams in the three-point bending test. It is not possible to use this 'forward' beam model for extraction of material parameters so an inverse model has been devised. This model is a basis for formulation of an inverse model that could be used for parameter extraction from laboratory tests. The key assumption in the developed inverse solution procedure is that some values in the formulation are known and comprised in the experimental data. The procedure includes measured data and its derivative, the formulation is nonlinear and solution is obtained from an iterative procedure. The proposed method is numerically validated in the example at the end of the paper and it is demonstrated that material parameters could be successfully recovered from measured data.

A Study on the Development Issues of Digital Health Care Medical Information (디지털 헬스케어 의료정보의 발전과제에 관한 연구)

  • Moon, Yong
    • Industry Promotion Research
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    • v.7 no.3
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    • pp.17-26
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    • 2022
  • As the well-being mindset to keep our minds and bodies free and healthy more than anything else in the society we live in is spreading, the meaning of health care has become a key part of the 4th industrial revolution such as big data, IoT, AI, and block chain. The advancement of the advanced medical information service industry is being promoted by utilizing convergence technology. In digital healthcare, the development of intelligent information technology such as artificial intelligence, big data, and cloud is being promoted as a digital transformation of the traditional medical and healthcare industry. In addition, due to rapid development in the convergence of science and technology environment, various issues such as health, medical care, welfare, etc., have been gradually expanded due to social change. Therefore, in this study, first, the general meaning and current status of digital health care medical information is examined, and then, developmental tasks to activate digital health care medical information are analyzed and reviewed. The purpose of this article is to improve usability to fully pursue our human freedom.

Modified AES having same structure in encryption and decryption (암호와 복호가 동일한 변형 AES)

  • Cho, Gyeong-Yeon;Song, Hong-Bok
    • Journal of Korea Society of Industrial Information Systems
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    • v.15 no.2
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    • pp.1-9
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    • 2010
  • Feistel and SPN are the two main structures in a block cipher. Feistel is a symmetric structure which has the same structure in encryption and decryption, but SPN is not a symmetric structure. In this paper, we propose a SPN which has a symmetric structure in encryption and decryption. The whole operations of proposed algorithm are composed of the even numbers of N rounds where the first half of them, 1 to N/2 round, applies a right function and the last half of them, (N+1)/2 to N round, employs an inverse function. And a symmetry layer is located in between the right function layer and the inverse function layer. In this paper, AES encryption and decryption function are selected for the right function and the inverse function, respectively. The symmetric layer is composed with simple matrix and round key addition. Due to the simplicity of the symmetric SPN structure in hardware implementation, the proposed modified AES is believed to construct a safe and efficient cipher in Smart Card and RFID environments where electronic chips are built in.

Deep Learning-Based Neural Distinguisher for PIPO 64/128 (PIPO 64/128에 대한 딥러닝 기반의 신경망 구별자)

  • Hyun-Ji Kim;Kyung-Bae Jang;Se-jin Lim;Hwa-Jeong Seo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.175-182
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    • 2023
  • Differential cryptanalysis is one of the analysis techniques for block ciphers, and uses the property that the output difference with respect to the input difference exists with a high probability. If random data and differential data can be distinguished, data complexity for differential cryptanalysis can be reduced. For this, many studies on deep learning-based neural distinguisher have been conducted. In this paper, a deep learning-based neural distinguisher for PIPO 64/128 is proposed. As a result of experiments with various input differences, the 3-round neural distinguisher for the differential characteristics for 0, 1, 3, and 5-rounds achieved accuracies of 0.71, 0.64, 0.62, and 0.64, respectively. This work allows distinguishing attacks for up to 8 rounds when used with the classical distinguisher. Therefore, scalability was achieved by finding a distinguisher that could handle the differential of each round. To improve performance, we plan to apply various neural network structures to construct an optimal neural network, and implement a neural distinguisher that can use related key differential or process multiple input differences simultaneously.

A Study on the Development of ESG Indicators for Sustainable Smart Ports (지속가능한 스마트 항만을 위한 ESG 지표 개발에 관한 연구)

  • Jae-Hoon Lee;Myung-Hee Chang
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.296-297
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    • 2022
  • A smart port refers to a port built based on digital technologies such as IoT, big data, AI, and block chain, and refers to a port that minimizes waste of time, space and resources as the only means of survival of the port. Sustainability refers to 'environmental, economic, and social characteristics that enable people to continue to use the environment, ecosystem, or publicly used resources'. It contains the meaning of 'future sustainability' that can be maintained in the future. In the face of the 4th industrial revolution, interest and realization of smart port construction and sustainability are actively progressing around the world. In this study, core indicators of the ESG (Enviornment, Social, Governance) area, which are key elements of sustainable smart ports, were developed,

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Formation and Inhibition of Cholesterol Oxidation Products (COPs) in Foods; An Overview (식품 내 콜레스테롤 산화 생성물(COPs)의 생성 및 억제; 개요)

  • Joo-Shin Kim
    • Journal of the Korean Applied Science and Technology
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    • v.40 no.5
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    • pp.1163-1175
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    • 2023
  • Cholesterol is prone to oxidation, which results in the formation of cholesterol oxidation products (COPs). This occurs because it is a monounsaturated lipid with a double bond on C-5 position. Cholesterol in foods is mostly non-enzymatically oxidized by reactive oxygen species (ROS)-mediated auto-oxidative reaction. The COPs are found in many common foods of animal-origin and are formed during their manufacture process. The formation of COPs is mainly related to the temperature and the heating time the food is processed, storage condition, light exposure and level of activator present such as free radical. The level of COPs in processed foods could reach up to 1-10 % of the total cholesterol depending on the foods. The most predominant COPs in foods including meat, eggs, dairy products as well as other foods of animal origin were 7-ketocholesterol, 7 α-hydroxycholesterol (7α-OH), 7β-hydroxycholesterol (7β-OH), 5,6α-epoxycholesterol (5,6α-EP), 5,6β-epoxycholesterol (5,6β-EP), 25-hydoxycholesterol (25-OH), 20-hydroxycholesterol (20-OH) and cholestanetriol (triol). They are mainly formed non-enzymatically by cholesterol autoxidation. The COPs are known to be potentially more hazardous to human health than pure cholesterol. The procedure to block cholesterol oxidation in foods should be similar to that of lipid oxidation inhibition since both cholesterol and lipid oxidation go through the same free radical mechanism. The formation of COPs in foods can be stopped by decreasing heating time and temperature, controlling storage condition as well as adding antioxidants into food products. This review aims to present, discuss and respond to articles and studies published on the topics of the formation and inhibition of COPs in foods and key factors that might affect cholesterol oxidation. This review may be used as a basic guide to control the formation of COPs in the food industry.

EDMFEN: Edge detection-based multi-scale feature enhancement Network for low-light image enhancement

  • Canlin Li;Shun Song;Pengcheng Gao;Wei Huang;Lihua Bi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.980-997
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    • 2024
  • To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.