• 한국IT서비스학회지
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• 제5권3호
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• pp.173-186
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• 2006

The local public organizations, to secure the Confidentiality, Integrity, Authentication and Non-Repudiation of cyber administrative environment is giving it a try to consolidate the official documents among them by standardizing all the documents into XML formats together with the establishment of the GPKI(Government Public Key Infrastructure). The Authentication System based on the PKI(Public Key Infrastructure) used by the GPKI, however, provides only the simple User Authentication and thus it results in the difficulty in managing the position, task, role information of various users required under the applied task environment of public organizations. It also has a limitation of not supporting the detailed access control with respect to the XML-based public documents.In order to solve these issues, this study has analyzed the security problems of Authentication and access control system used by the public organizations and has drawn the means of troubleshoot based on the analysis results through the scenario and most importantly it suggests the access control model applied with PMI and SAML and XACML to solve the located problem.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.212-222
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• 2021

Multiple waves of COVID-19 highlighted one crucial aspect of this pandemic worldwide that factors affecting the spread of COVID-19 infection are evolving based on various regional and local practices and events. The introduction of vaccines since early 2021 is expected to significantly control and reduce the cases. However, virus mutations and its new variant has challenged these expectations. Several countries, which contained the COVID-19 pandemic successfully in the first wave, failed to repeat the same in the second and third waves. This work focuses on COVID-19 pandemic control and management in Saudi Arabia. This work aims to predict new cases using deep learning using various important factors. The proposed method is called Deep Learning and Dynamic Weighing-based (DLDW) COVID-19 cases prediction method. Special consideration has been given to the evolving factors that are responsible for recent surges in the pandemic. For this purpose, two weights are assigned to data instance which are based on feature importance and dynamic weight-based time. Older data is given fewer weights and vice-versa. Feature selection identifies the factors affecting the rate of new cases evolved over the period. The DLDW method produced 80.39% prediction accuracy, 6.54%, 9.15%, and 7.19% higher than the three other classifiers, Deep learning (DL), Random Forest (RF), and Gradient Boosting Machine (GBM). Further in Saudi Arabia, our study implicitly concluded that lockdowns, vaccination, and self-aware restricted mobility of residents are effective tools in controlling and managing the COVID-19 pandemic.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.86-90
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• 2021

The article assesses the level of navigation safety, in theoretical terms, defines the complexity of managing navigational risks in practice. The issues of assessing the navigational safety have been studied due to the importance and relevance of the issue in question, however, due to the great complexity of the problem under consideration, the article considers and indicates the directions for the development of the solution of the given direction, where, first of all, it became necessary to analyze the issue of assessing the levels of navigation risks when navigating vessels of various types in difficult navigation conditions.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.196-202
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• 2021

DNA sequencing provides fundamental data in genomics, bioinformatics, biology and many other research areas. With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Those large volumes of data also require a fast transmission, effective storage, superior functionality and provision of quick access to any record. Data storage costs have a considerable proportion of total cost in the formation and analysis of DNA sequences. In particular, there is a need of highly control of disk storage capacity of DNA sequences but the standard compression techniques unsuccessful to compress these sequences. Several specialized techniques were introduced for this purpose. Therefore, to overcome all these above challenges, lossless compression techniques have become necessary. In this paper, it is described a new DNA compression mechanism of pattern matching extended Compression algorithm that read the input sequence as segments and find the matching pattern and store it in a permanent or temporary table based on number of bases. The remaining unmatched sequence is been converted into the binary form and then it is been grouped into binary bits i.e. of seven bits and gain these bits are been converted into an ASCII form. Finally, the proposed algorithm dynamically calculates the compression ratio. Thus the results show that pattern matching extended Compression algorithm outperforms cutting-edge compressors and proves its efficiency in terms of compression ratio regardless of the file size of the data.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.297-307
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• 2021

In the vibrant environment, documentation and managing systems are maintained autonomously through education foundations, book materials and libraries at the same time as information are not voluntarily accessible in a centralized location. At the moment Libraries are providing online resources and services for education activities. Moreover, libraries are applying outlets of social media such as Facebook as well as Instagrams to preview their services and procedures. Librarians with the assistance of promising tools and technology like analytics software are capable to accumulate more online information, analyse them for incorporating worth to their services. Thus Libraries can employ big data to construct enhanced decisions concerning collection developments, updating public spaces and tracking the purpose of library book materials. Big data is being produced due to library digitations and this has forced restrictions to academicians, researchers and policy creator's efforts in enhancing the quality and effectiveness. Accordingly, helping the library clients with research articles and book materials that are in line with the users interest is a big challenge and dispute based on Taibah university in Saudi Arabia. The issues of this domain brings the numerous sources of data from various institutions and sources into single place in real time which can be time consuming. The most important aim is to reduce the time that lapses among the authentic book reading and searching the specific study material.

• 정보보호학회논문지
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• 제15권6호
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• pp.71-80
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• 2005

향후 다양한 인터넷 응용 프로그램들은 멀티캐스트 그룹 통신에 기반을 두게 될 것이며, 따라서 그룹 멤버들의 빈번한 가입과 탈퇴를 효율적으로 대처하기 위한 그룹키 관리기법이 요구된다. 본 논문에서는 기존의 개별 키 갱신기법들을 일괄 키 갱신 기법으로 확장하여 제안하고, 기존의 기법들과 제안된 기법을 키 서버에 의해 수행되는 암호화 및 일방향 해쉬 함수의 횟수 그리고 멀티캐스트 메시지의 크기 측면에서 성능을 비교 분석한다. 비교 분석에 있어서는, 다중 탈퇴자가 존재하는 상황에서 그들에 의해 초래되는 키 갱신 비용을 확률론적인 접근법을 기반으로 평균치를 계산하였다.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.324-330
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• 2022

At the present stage of the world economic development, a new economic system is being formed, in which non-economic values, in particular environmental and social parameters, have become widespread. A new vision of economic activity is being formed, which acquires the qualities of Smart-economy. The purpose of this paper is reveal the features of managing the development of smart cities as specific entities of the Smart-economy. New functions of economic entities are formed within the framework of the Smart-economy concept, while their role and weight in the localities' activity or formation have changed. Determining that the key trends in the Smart-economy development are such as digitalization, greening, socialization, institutionalization, and urbanization, this is necessary to note that all these trends are most active in the formation of urban ecosystems. These trends are determined by the general population growth and the urban population growth, which requires considerable attention to planning each city's development itself. Such planning could ensure the comfort of living for all its inhabitants, quality, safe, and modern life. The Smart-city's key elements and the intellectualized approach implementation planes to the decision of these or those tasks are definedIt is determined that a new ecosystem of governance is being formed.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.335-343
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• 2022

The article analyzes the features of innovation and investment activities of enterprises in the context of digitalization to increase their competitiveness in the international market. Ukraine's position on the Global Innovation Index is assessed. The interrelation of management functions in the context of innovation and investment activities of enterprises is substantiated. The structure of sources of financing of innovative activity of industrial enterprises is analyzed. Trends in changes in the volume of foreign direct investment and capital investment in Ukraine are assessed. It is determined that the level of innovative development of enterprises is determined by the level of their investment support, which is determined by the level of their investment attractiveness. The components of the strategy of investment attractiveness of enterprises are outlined. Determining factors in the implementation of innovation and investment policy of enterprises are identified and the main stages that should include the processes of managing innovation and investment activities of enterprises in the context of digitalization.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• International Journal of Computer Science & Network Security
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• 제23권6호
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• pp.59-67
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• 2023

The healthcare industry continues to adopt and integrate smart technology in its operations, from medical devices to managing operations. However, the adoption curve has not been smooth, and the historical record of technology adoption in the Kingdom of Saudi Arabia reveals the existence of both known and unknown issues. This review paper is aimed to explain the influences and barriers present in the Saudi healthcare sector affecting IoT technology adoption. A comprehensive discussion of the literature illustrated that Vision 2030, the privatisation trend, transformation in disease patterns and ageing, issues in management and increasing public awareness are the key drivers that may influence the need for the medical Internet of Things (mIoT) in Saudi healthcare. However, based on the past trend, the introduction and adoption of mIoT will likely experience issues such as noncompliance from doctors and nurses due to negative beliefs, lack of knowledge and inadequate perception of effort requirements. Thus, in-depth research of the factors associated with mIoT technology adoption is suggested for a smooth transition.