• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.99-109
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• 2021

With the recent development of ICT, information exchange through data communication network is increasing. Cryptography is widely used as the base technology to protect it. The initial cryptography technology was developed for military use and authorized only by the nation in the past. However, nowadays, much of the authority was unwillingly transferred to the private due to the pervasive use of ICT. As a result, there have been conflicts between the private demand to use cryptography and the nation's authority. In this paper, we survey the conflicts between nations and the private in the process of formulating the cryptography policy. Morever, we investigate the reality of the cryptography policy in Korea. Our investigations are expected to help the government apply cryptographic control policy in a balanced manner and plan development of cryptography industries. Lastly, we propose a need to establish a cryptanalysis organization and to legislate a legal sanction against fraudulent use of cryptography.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.1-11
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• 2021

Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.

• The Plant Pathology Journal
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• v.37 no.2
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• pp.152-161
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• 2021

Sugar beet (Beta vulgaris L.) is known as a key product for agriculture in several countries across the world. Beet soil-borne virus (BSBV) triggers substantial economic damages to sugar beet by reducing the quantity of the yield and quality of the beet sugars. We conducted the present study to report the complete genome sequences of two BSBV isolates in Turkey for the first time. The genome organization was identical to those previously established BSBV isolates. The tripartite genome of BSBV-TR1 and -TR3 comprised a 5,835-nucleotide (nt) RNA1, a 3,454-nt RNA2, and a 3,005-nt RNA3 segment. According to sequence identity analyses, Turkish isolates were most closely related to the BSBV isolate reported from Iran (97.83-98.77% nt identity). The BSBV isolates worldwide (n = 9) were phylogenetically classified into five (RNA-coat protein read through gene [CPRT], TGB1, and TGB2 segments), four (RNA-rep), or three (TGB3) lineages. In genetic analysis, the TGB3 revealed more genetic variability (Pi = 0.034) compared with other regions. Population selection analysis revealed that most of the codons were generally under negative selection or neutral evolution in the BSBV isolates studied. However, positive selection was detected at codon 135 in the TGB1, which could be an adaptation in order to facilitate the movement and overcome the host plant resistance genes. We expect that the information on genome properties and genetic variability of BSBV, particularly in TGB3, TGB1, and CPRT genes, assist in developing effective control measures in order to prevent severe losses and make amendments in management strategies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.914-921
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• 2022

The International Maritime Organization (IMO) has set a goal of reducing ship's carbon dioxide emissions by 70% and greenhouse gas emissions by 50% by 2050 compared to 2008. Shipowners and shipyards are promoting various R&D activities such as LNG propulsion, ammonia propulsion, electric propulsion, CO₂ capture, and shaft generators as a way to satisfy this problem. The dual shaft generator has the advantage that it can be directly applied to an existing ship through remodeling. In this paper, the total fuel reduction rate that can be obtained by applying the shaft generator to the existing ship was verified through simulation. For this purpose, the size of the medium-sized ship was defined, and the governor, diesel engine, propeller, torque switch, generator for shaft generator, propulsion motor for shaft generator, and ship model were modeled and simulated.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.107-114
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• 2022

Delegation is a powerful mechanism that allocates access rights to users to provide flexible and dynamic access control decisions. It is also particularly useful in a distributed environment. Among the representative delegation models, the RBDM0 and RDM2000 models are role delegation as the user to user delegation. However, In RBAC, the concept of inheritance of the role class is not well harmonized with the management rules of the actual corporate organization. In this paper, we propose an Adding Attributes on Permission-Based Delegation Model (ABDM) that guarantees the permanence of delegated permissions. It does not violate the separation of duty and security principle of least privilege. ABDM based on RBAC model, supports both the role to role and user to user delegation with an attribute. whenever the delegator wants the permission can be withdrawn, and A delegator can give permission to a delegatee.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.445-466
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• 2022

As everything linking to the internet, people can subscribe to various services from a service provider to facilitate their lives through the Internet of Things (IoT). An obligatory thing for the service provider is that they should push the service data safely and timely to multiple IoT terminal devices regularly after the IoT devices accomplishing the service subscription. In order to control the service message received by the legal devices as while as keep the confidentiality of the data, the public key encryption algorithm is utilized. While the existing public encryption algorithms for push service are too complicated for IoT devices, and almost of the current subscription schemes based on push mode are relying on centralized organization which may suffer from centralized entity corruption or single point of failure. To address these issues, we design a secure subscription-push service scheme based on blockchain and edge computing in this article, which is decentralized with secure architecture for the subscription and push of service. Furthermore, inspired by broadcast encryption and multicast encryption, a new encryption algorithm is designed to manage the permissions of IoT devices together with smart contract, and to protect the confidentiality of push messages, which is suitable for IoT devices. The edge computing nodes, in the new system architecture, maintain the blockchain to ensure the impartiality and traceability of service subscriptions and push messages, meanwhile undertake some calculations for IoT devices with limited computing power. The legalities of subscription services are guaranteed by verifying subscription tags on the smart contract. Lastly, the analysis indicates that the scheme is reliable, and the proposed encryption algorithm is safe and efficient.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.102-114
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• 2021

Biofouling represents an important problem in the shipping industry since it causes the increase in surface roughness. The most of ships in the current world fleet do not have good coating condition which represents an important problem due to strict rules regarding ship energy efficiency. Therefore, the importance of the control and management of the hull and propeller fouling is highlighted by the International Maritime Organization and the maintenance schedule optimization became valuable energy saving measure. For adequate implementation of this measure, the accurate prediction of the effects of biofouling on the hydrodynamic characteristics is required. Although computational fluid dynamics approach, based on the modified wall function approach, has imposed itself as one of the most promising tools for this prediction, it requires significant computational time. However, during the maintenance schedule optimization, it is important to rapidly predict the effect of biofouling on the ship hydrodynamic performance. In this paper, the effect of biofilm on the ship hydrodynamic performance is studied using the proposed performance prediction method for three merchant ships. The applicability of this method in the assessment of the effect of biofilm on the ship hydrodynamic performance is demonstrated by comparison of the obtained results using the proposed performance prediction method and computational fluid dynamics approach. The comparison has shown that the highest relative deviation is lower than 4.2% for all propulsion characteristics, lower than 1.5% for propeller rotation rate and lower than 5.2% for delivered power. Thus, a practical tool for the estimation of the effect of biofouling with lower fouling severity on the ship hydrodynamic performance is developed.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• Genomics & Informatics
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• v.19 no.4
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• pp.39.1-39.8
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• 2021

Tamoxifen (TAM) is an anticancer drug used to treat estrogen receptor (ER)-positive breast cancer. However, its ER-independent cytotoxic and antifungal activities have prompted debates on its mechanism of action. To achieve a better understanding of the ER-independent antifungal action mechanisms of TAM, we systematically identified TAM-sensitive genes through microarray screening of the heterozygous gene deletion library in fission yeast (Schizosaccharomyces pombe). Secondary confirmation was followed by a spotting assay, finally yielding 13 TAM-sensitive genes under the drug-induced haploinsufficient condition. For these 13 TAM-sensitive genes, we conducted a comparative analysis of their Gene Ontology (GO) 'biological process' terms identified from other genome-wide screenings of the budding yeast deletion library and the MCF7 breast cancer cell line. Several TAM-sensitive genes overlapped between the yeast strains and MCF7 in GO terms including 'cell cycle' (cdc2, rik1, pas1, and leo1), 'signaling' (sck2, oga1, and cki3), and 'vesicle-mediated transport' (SPCC126.08c, vps54, sec72, and tvp15), suggesting their roles in the ER-independent cytotoxic effects of TAM. We recently reported that the cki3 gene with the 'signaling' GO term was related to the ER-independent antifungal action mechanisms of TAM in yeast. In this study, we report that haploinsufficiency of the essential vps54 gene, which encodes the GARP complex subunit, significantly aggravated TAM sensitivity and led to an enlarged vesicle structure in comparison with the SP286 control strain. These results strongly suggest that the vesicle-mediated transport process might be another action mechanism of the ER-independent antifungal or cytotoxic effects of TAM.

• Genomics & Informatics
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• v.20 no.3
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• pp.32.1-32.15
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• 2022

Malaria is a life-threatening disease, and Africa is still one of the most affected endemic regions despite years of policy to limit infection and transmission rates. Further, studies into the variable efficacy of the vaccine are needed to provide a better understanding of protective immunity. Thus, the current study is designed to delineate the effect of each dose of vaccine on the transcriptional profiles of subjects to determine its efficacy and understand the molecular mechanisms underlying the protection this vaccine provides. Here, we used gene expression profiles of pre and post-vaccination patients after various doses of RTS,S based on samples collected from the Gene Expression Omnibus datasets. Subsequently, differential gene expression analysis using edgeR revealed the significantly (false discovery rate < 0.005) 158 downregulated and 61 upregulated genes between control vs. controlled human malaria infection samples. Further, enrichment analysis of significant genes delineated the involvement of CCL8, CXCL10, CXCL11, XCR1, CSF3, IFNB1, IFNE, IL12B, IL22, IL6, IL27, etc., genes which found to be upregulated after earlier doses but downregulated after the 3rd dose in cytokine-chemokine pathways. Notably, we identified 13 cytokine genes whose expression significantly varied during three doses. Eventually, these findings give insight into the dual role of cytokine responses in malaria pathogenesis. The variations in their expression patterns after various doses of vaccination are linked to the protection as it decreases the severe inflammatory effects in malaria patients. This study will be helpful in designing a better vaccine against malaria and understanding the functions of cytokine response as well.