• 제목/요약/키워드: Security Strategies

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A Study on the Policy Alternatives for Intelligent National Territorial Disaster Prevention in Preparation for Future Disaster (미래형 재난에 대비한 국토방재 지능화 정책대안 고찰 연구)

  • Byoung Jae Lee
    • Journal of Korean Society of Disaster and Security
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    • v.16 no.1
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    • pp.37-48
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    • 2023
  • The possibility of a super-large disaster is increasing due to changes in national territory, urban space and social environment, extreme weather conditions due to climate change, and paralysis of national infrastructure due to natural disasters. In this study, in order to support the systematic establishment of national territorial disaster prevention strategies for future disasters, alternatives to intelligent national territorial disaster prevention policies for future disasters were considered. Changes in the national environment related to future disasters, domestic and foreign prior studies and policy trends related to national disaster prevention, and studies related to the national disaster management system were investigated, and institutional and technical policy alternatives were derived. As a policy alternative, it was suggested that the creation of a self-adapting national territory for future disasters should be systematized and continuously supported through a technically intelligent decision-making support system.

Personalized Diabetes Risk Assessment Through Multifaceted Analysis (PD- RAMA): A Novel Machine Learning Approach to Early Detection and Management of Type 2 Diabetes

  • Gharbi Alshammari
    • International Journal of Computer Science & Network Security
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    • v.23 no.8
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    • pp.17-25
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    • 2023
  • The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.

Strategies to improve irrigation water management for rice production in Pulangui River Irrigation System

  • Siem, Paul Roderick M.;Ahmad, Mirza Junaid;Choi, Kyung-Sook
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.509-509
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    • 2022
  • Rice has always been the anchor of food security in the Philippines and the government is adamant about sustaining rice production by ensuring reliable irrigation water availability. Among the numerous irrigation schemes, the importance of the Pulangui River Irrigation System (PRIS) is undeniable, as it is the largest and primary irrigation source for rice production areas which are considered the food basket in Northern Mindanao. However, the ageing irrigation structures, unlined canals, long-standing water delivery systems, and climate change are compromising the performance of PRIS; and every year, during the dry and wet season, the maximum rice irrigable area is not achieved. From the field-scale water management perspective, untimely irrigation application, an unregulated roster of turn for irrigation among farmers, and the traditional practice of flooding the rice fields are the main causes of substantial water losses in conveyance, distribution, and farm application of irrigation water. Hence, proper irrigation scheduling is crucial to cultivate the maximum irrigable area by ensuring equity among the farmers and to increase the water use efficiency and yield. In this study, the FAO single crop coefficient approach was adopted to estimate rice water requirements, which were subsequently used to suggest appropriate irrigation schedules based on the recommended field-scale rice cultivation practices. The study results would improve the irrigation system management in the study area by facilitating in regulating the canal water flows and releases according to suggested irrigation schedules that could lead to increased benefited area, yield, and water efficiency without straining the available water resources.

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The Impact of Information Security(IS) Organizational Justice on Employee IS Value Congruence and IS Voice Behavior: Exploring the Role of Susceptibility to Interpersonal Influence (조직의 정보보안 공정성이 개인의 정보보안 관련 가치 일치 및 제언 행동에 미치는 영향: 대인 간 영향 민감성의 적용)

  • Hwang, Inho
    • The Journal of Information Systems
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    • v.32 no.4
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    • pp.1-28
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    • 2023
  • Purpose Recently, organizations have been allocating significant financial resources toward the implementation of new technologies and stringent information security (IS) policies in order to enhance IS. However, the potential for IS threats from internal sources within organizations remains high. This study proposes a mechanism whereby the organization's IS environment (organizational justice) enhances employees' perception of IS value congruence and encourages their voice behavior. Furthermore, this study validates that an individual's susceptibility to interpersonal influence can reinforce the relationship between the aforementioned factors and voice behavior. Design/methodology/approach We utilized AMOS 22.0 and Process 3.1 to validate the research model and hypotheses. The data was gathered from 435 employees employed in South Korean firms that implemented IS policies in their work. Structural equation modeling was employed to examine the relationship between organizational justice, value congruence, and voice behavior, and the interaction effect was confirmed by incorporating model 1 of Process 3.1 for the hypothesis pertaining to susceptibility to interpersonal influence. Findings The findings of this study indicate that organizational justice has a positive impact on voice behavior, which is further enhanced by value congruence. Furthermore, the influence of organizational justice and value congruence on voice behavior is moderated by susceptibility to information influence, while susceptibility to normative influence only moderates the effect of organizational justice. These results provide valuable insights for organizations in developing customized information systems strategies that effectively promote employees' voice behaviors.

Issues of Harmonization of ISO 9001 Standard and the Law 09-08. Protection of Personal Data in Morocco: Potentials and Risks

  • Adil CHEBIR ;Ibtissam EL MOURY;Adil ECHCHELH;Omar TAOUAB
    • International Journal of Computer Science & Network Security
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    • v.23 no.10
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    • pp.57-66
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    • 2023
  • Since 2009, Morocco has had a law governing the processing of personal data, the law 09-08, and a supervisory authority, the CNDP (National Commission for the Protection of Personal Data). Since May 2018, the European General Regulation on the Protection of Personal Data (GDPR) entered into force, which applies outside the EU in certain cases and therefore to certain Moroccan companies. The question of the protection of personal data is primarily addressed to the customer. The latter may not only be a victim of crime linked to ICT, but also have to face risks linked to the collection and abusive processing of his personal data by the private and public sectors. Often the customer does not really know how their data is stored, nor for how long and for what purpose. This fact raises the question of satisfying customer requirements, in particular for organizations that have adopted a quality approach based on ISO 9001 standard.In order to master these constraints, Moroccan companies have to adopt strategies based on modern quality management techniques, especially the adoption of principles issued from the international standard ISO 9001 while being confirmed by the law 09-08. It is through ISO 9001 and the law 09-08 that these companies can refer to recognized approaches in terms of quality and compliance. The major challenge for these companies is to have a Quality approach that allows the coexistence between the law 09-08 and ISO 9001 standard and this article deals within this specific context.

Advancements in Drone Detection Radar for Cyber Electronic Warfare (사이버전자전에서의 드론 탐지 레이다 운용 발전 방안 연구)

  • Junseob Kim;Sunghwan Cho;Pokki Park;Sangjun Park;Wonwoo Lee
    • Convergence Security Journal
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    • v.23 no.3
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    • pp.73-81
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    • 2023
  • The progress in science and technology has widened the scope of the battlefield, leading to the emergence of cyber electronic warfare that exploits electromagnetic waves and networks. Drones have become more important due to advancements in battery technology and navigation systems. Nevertheless, tackling drone threats comes with its own set of difficulties. Radar plays a vital role in detecting drones, offering long-range capabilities and independence from weather conditions. However, the battlefield presents unique challenges like dealing with high levels of signal noise and ensuring the safety of the detection assets. This paper proposes various approaches to improve the operation of drone detection radar in cyber electronic warfare, with a focus on enhancing signal processing techniques, utilizing low probability of interception (LPI) radar, and implementing optimized deployment strategies.

Cyber Threat Intelligence Traffic Through Black Widow Optimisation by Applying RNN-BiLSTM Recognition Model

  • Kanti Singh Sangher;Archana Singh;Hari Mohan Pandey
    • International Journal of Computer Science & Network Security
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    • v.23 no.11
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    • pp.99-109
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    • 2023
  • The darknet is frequently referred to as the hub of illicit online activity. In order to keep track of real-time applications and activities taking place on Darknet, traffic on that network must be analysed. It is without a doubt important to recognise network traffic tied to an unused Internet address in order to spot and investigate malicious online activity. Any observed network traffic is the result of mis-configuration from faked source addresses and another methods that monitor the unused space address because there are no genuine devices or hosts in an unused address block. Digital systems can now detect and identify darknet activity on their own thanks to recent advances in artificial intelligence. In this paper, offer a generalised method for deep learning-based detection and classification of darknet traffic. Furthermore, analyse a cutting-edge complicated dataset that contains a lot of information about darknet traffic. Next, examine various feature selection strategies to choose a best attribute for detecting and classifying darknet traffic. For the purpose of identifying threats using network properties acquired from darknet traffic, devised a hybrid deep learning (DL) approach that combines Recurrent Neural Network (RNN) and Bidirectional LSTM (BiLSTM). This probing technique can tell malicious traffic from legitimate traffic. The results show that the suggested strategy works better than the existing ways by producing the highest level of accuracy for categorising darknet traffic using the Black widow optimization algorithm as a feature selection approach and RNN-BiLSTM as a recognition model.

Time series models for predicting the trend of voice phishing: seasonality and exogenous variables approaches (보이스피싱 발생 추이 예측을 위한 시계열 모형 연구: 계절성과 외생변수 활용)

  • Da-Yeon Kang;Seung-Yeon Lee;Eunju Hwang
    • Convergence Security Journal
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    • v.24 no.2
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    • pp.151-160
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    • 2024
  • In recent years with high interest rates and inflations, which worsen people's lives, voice phishing crimes also increase along with damage. Voice phishing that becomes more evolved by technology developments causes serious financial and mental damage to victims. This work aims to study time series models for its accurate prediction. ARIMA, SARIMA and SARIMAX models are compared. As exogenous variables, the amount of damages and the numbers of arrests and criminals are adopted. Forecasting performances are evaluated. Prediction intervals are constructed along with empirical coverages, which justify the superiority of the model. Finally, the numbers of voice phishing up to December 2024 are predicted, through which we expect the establishment of future prevention strategies for voice phishing.

Social Networks As A Tool Of Marketing Communications

  • Nataliia Liashuk
    • International Journal of Computer Science & Network Security
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    • v.23 no.12
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    • pp.137-144
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    • 2023
  • The relevance of the research topic lies in the necessity to use social networks as innovative tools of marketing communications. A wide audience and the ability to segment the market for a specific consumer determine the construction of a corporate strategy, which will be based on using the social networking approach. The spread of the global coronavirus pandemic has led to the rapid development of remote communication channels between the company and the customer. The issue of using marketing tools in social networks acquires the most urgent importance in the modern world of the introduction and implementation of the company's marketing strategies. The purpose of the academic paper is to study the use of social networks as features of implementing the marketing campaign. Social networks are the result of the development of digital technologies and the processes of creating an information society involved in the digital space. The objectives of the research are to analyse the opportunity of using social networks as a tool for marketing communications and their implementation at the level of its widespread use by enterprises and establishments. It is significant to create an advertising campaign by defining the target audience and outlining the key aspects, on which the company is focused. The research methodology consists in determining the theoretical and methodological approaches to the essence of introducing social networks and their practical importance in the implementation of marketing activities of companies. The obtained results can significantly improve the quality of functioning of modern enterprises and organizations that plan to master a new market segment or gain competitive advantages in the existing one. The academic paper examines the essence of social networks as a tool of marketing communications. The key principles of the development of digital social platforms were revealed. The quality of implementing the advertising campaign in the social network was studied, and further prospects for the development of using social networks as a component of the marketing strategy were outlined. Therefore, the academic paper analyses the problems of using social networks as a marketing tool.

Corporate Social Responsibility in Modern Transnational Corporations

  • Vitalii Nahornyi;Alona Tiurina;Olha Ruban;Tetiana Khletytska;Vitalii Litvinov
    • International Journal of Computer Science & Network Security
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    • v.24 no.5
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    • pp.172-180
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    • 2024
  • Since the beginning of 2015, corporate social responsibility (CSR) models have been changing in connection with the trend towards the transition of joint value creation of corporate activities and consideration of stakeholders' interests. The purpose of the academic paper lies in empirically studying the current practice of social responsibility of transnational corporations (TNCs). The research methodology has combined the method of qualitative analysis, the method of cases of agricultural holdings in emerging markets within the framework of resource theory, institutional theory and stakeholders' theory. The results show that the practice of CSR is integrated into the strategy of sustainable development of TNCs, which determine the methods, techniques and forms of communication, as well as areas of stakeholders' responsibility. The internal practice of CSR is aimed at developing norms and standards of moral behaviour with stakeholders in order to maximize economic and social goals. Economic goals are focused not only on making a profit, but also on minimizing costs due to the potential risks of corruption, fraud, conflict of interest. The system of corporate social responsibility of modern TNCs is clearly regulated by internal documents that define the list of interested parties and stakeholders, their areas of responsibility, greatly simplifying the processes of cooperation and responsibility. As a result, corporations form their own internal institutional environment. Ethical norms help to avoid the risks of opportunistic behaviour of personnel, conflicts of interest, cases of bribery, corruption, and fraud. The theoretical value of the research lies in supplementing the theory of CSR in the context of the importance of a complex, systematic approach to integrating the theory of resources, institutional theory, theory of stakeholders in the development of strategies for sustainable development of TNCs, the practice of corporate governance and social responsibility.