Area Of Security Research Articles

Application and prospect of landscape ecology in territorial spatial planning.

Territorial spatial planning could achieve the integration of various plans, resulting in a unified "multi-plan integration" map. Such planning emphasizes the efficient use of territorial spatial patterns and structures to ensure functional perfection, and serves as the spatial framework for building a modern socialist country, particularly in the areas of ecological security and ecological civilization. The past few decades have seen rapid advances in the development of landscape ecology in China. The core concept of "pattern-process-function" has gained significant progress and been widely applied in the initial phase of territorial spatial planning at various levels. We outlined the advancements in the territorial spatial planning system and the core research theories and technologies in landscape ecology. We discussed the progress and shortcomings of key theories and methods of landscape ecology in practical applications of territorial spatial planning, such as ecological security patterns, pattern and process, and scale effects. We proposed the future application of landscape ecology theories and technologies in territorial spatial planning, including overall ecological effects, scale effects, and regional ecological network optimization. Future developments in landscape ecology, especially research on the "human-place-ecology" coupling based on the latest Big Data and AI technology for sustainable development, will provide robust theoretical and methodological supports for the scientific formulation of territorial spatial planning in China.

Optimalisasi Pagar Perimeter terhadap Standart Keamanan oleh Petugas Avsec di Daerah Keamanan Terbatas Bandar Udara Internasional Adi Soemarmo Boyolali

A limited security area is an area used for aircraft movement activities, employee or staff movement, and work equipment for flight activities, passenger and baggage movement that will board the aircraft, and vital installations/objects that are directly related to aircraft operations. The purpose of this study was to determine whether the perimeter fence of the limited security area of Adi Soemarmo International Airport was in accordance with applicable provisions and what efforts were made by Airport Security officers to meet the perimeter fence standards in the limited security area of Adi Soemarmo Boyolali International Airport. This study uses a qualitative approach with the types and sources of data, namely primary data and secondary data. This research was conducted at Adi Soemarmo Boyolali International Airport and the time of implementation of this research was carried out from August 1 to January 11 at the Airport Security (AVSEC) unit. The results of this study are that the condition of the perimeter fence of the limited security area of Adi Soemarmo International Airport is not in accordance with applicable regulations. This can disrupt flight activities and threaten flight safety. Efforts made by Airport Security officers for security are patrols in the perimeter fence area and approaches to the community to prevent unlawful acts.

China’s interdependent positioning in the semiconductor global value chain

ABSTRACT The semiconductor global value chain (GVC) which was established by global lead companies and their strategic suppliers is now facing significant disruption because of geopolitical tensions between the US and China. As semiconductor production became offshored to East Asia, China’s growing market for semiconductors associated with its role as a major electronics assembly location facilitated its integration into the global value chain for lower value added functions such as assembly and packaging. Together with its high level of optimisation, the GVC is also characterised by significant oligopolies of intellectual property resulting in an overall asymmetric interdependence between locations in advanced and emerging regions. Because of the vital role of the semiconductor sector in areas of national security and within the technology sector more widely, China seeks to develop greater self-reliance in semiconductors at a time when its integration in the global value chain is facing significant threats.

Securing Data Transmission from Adversaries in Cybersecurity WSN Using Efficient Key Management Techniques

Concern over cyber security is becoming more and more prevalent in today's international politics. National security is now evaluated not only in terms of military might or economic might, but also in terms of technological innovation. The fact that today's society is heavily dependent on computer communication and control systems, which opens up infinite opportunities, shows how important technology is in the national security area. By effectively changing the keys, the suggested work aimed to provide WSN with complicated security solutions that would ensure data integrity, security, and genuine transmission for many additional network operations through structured cryptography approaches. The study's protective measures can be applied to a variety of WSN configurations, including heterogeneous WSNs with and without mobility aid and static homogeneous WSNs. Because WSN is more limited to hardware resources, not all applications can be protected using the same method.

An intrusion detection method combining variational auto-encoder and generative adversarial networks

Deep learning is a crucial research area in network security, particularly when it comes to detecting network attacks. While some deep learning algorithms have shown promising results in distinguishing between normal and abnormal traffic, identifying different types of imbalanced anomalous traffic data is still a challenging task at present. To enhance the detection performance of unbalanced anomalous flows, we propose a new intrusion detection architecture based on a variational auto-encoder (VAE) and generative adversarial networks (GAN) in this research. Firstly, we present the VAE-WGAN model, which combines the advantages of VAE and GAN and enables us to generate data with predefined labels to balance the original training dataset. In the intrusion detection phase, we use a hybrid neural network model based on stacked Long Short-Term Memory (LSTM) and Multi-Scale Convolutional Neural Network (MSCNN). Stacked LSTM and MSCNN networks can extract network characteristics at different depths and scales, and subsequent feature fusion is used to increase network attack detection rates. Finally, the results from the NSL-KDD and AWID datasets indicate that the proposed network intrusion detection model improves the accuracy of network attack detection. The model outperforms other existing intrusion detection approaches in terms of accuracy, precision, recall, and f1-score, obtaining 83.45% accuracy and 83.69% f1-score on the NSL-KDD dataset. Moreover, it attains an accuracy and f1-score exceeding 98.9% on the AWID dataset.

Leveraging Azure And AWS Advisor Scores for Improved Cloud Governance and Cost Management

Cloud governance and cost management become major concerns when shifting to cloud environments [Figure 1] Because cloud resources are dynamic, frameworks for evaluation and optimization that need the least amount of financial outlay are required. In this sense, cloud resource management has been made easier by built-in tools like Advisor scores, which present a list of recommendations for improved usage, on platforms like AWS and Azure. The finest practices in the areas of security, performance, dependability, and cost efficiency are highlighted by these scores. Furthermore, if a company utilizes these ratings consistently, it can discover opportunities for significant cost savings in addition to improving governance, policy, and regulatory compliance. This paper explores how Azure and AWS Advisor ratings may be used as useful tools to improve cloud governance and simplify cost management. By doing this, it aims to offer a critical perspective on how these technologies could change how organizations optimize their use of cloud resources. These ratings, when combined with governance frameworks, will encourage enterprises to manage cloud resources more proactively and methodically [12]. The organization will maintain compliance with industry standards thanks to this systematic examination, which will lead to unmatched security and dependability as well as cost control. Eventually, the company will be able to safely use AWS and Azure advisor scores to optimize cloud operations, maintaining the cloud's reliability, security, and efficiency while keeping it in line with strategic goals

Intensive care unit nursing workload estimation in smart hospitals

PurposeThe objectives of the proposed model are: aiding nursing staff in documentation tasks, which can be onerous and stressful; and helping management by offering an estimate of the nursing workload, which can be considered for administrative purposes, such as staff scheduling.Design/methodology/approachAn exploratory-descriptive study was conducted in order to identify, investigate, and describe the problem of documenting nursing activities and workload estimation in an intensive care unit. Technological solutions were explored, and models were proposed to address these issues.FindingsCross-dataset experiments were performed, and the model was able to offer an adequate estimate of the nursing workload. The results suggest that continuous retraining is essential for maintaining high accuracy. While the proposed model was considered in the context of an adult ICU, it can be adapted to other contexts, such as elderly care.Research limitations/implicationsWhile the proposed solution seems promising, further research is required, such as deploying this system in an ICU and facing challenges in the areas of computer security, medical ethics, and patient data privacy. More patients’ variables could also be collected to improve the workload estimates.Originality/valueNursing workload assessment is critical to improve the cost-benefit ratio in health care, offer high-quality patient care, and reduce unnecessary expenses, and this process is usually manual. An automated device can automatically document the amount of time spent in patient care activities in a more transparent, efficient, and accurate manner, freeing staff for more urgent activities and keeping management better informed about day-to-day nursing operations.

The Application of GPS-Based Friend/Foe Localization and Identification to Enhance Security in Restricted Areas.

This paper is devoted to the application of object localization and identification with information combined from a radar system and a dedicated portable/mobile electronic device equipped with a global positioning system (GPS) receiver. This device is able to provide object's (staff member, and staff vehicle) rough location and identification. Such systems are required in very restrictive security areas like airports (e.g., open-air area and apron). Currently, the outdoor area of the airport is typically protected by a surveillance system operated by security guards. Surveillance systems are composed of different sensors, video and infrared cameras, and microwave radars. The sheer number of events generated via the system can lead to fatigue among staff, potentially resulting in the omission of critical events. To address this issue, we propose an electronic system equipped with a wireless module and a GPS module. This approach enables automatic identification of objects through the fusion of data from two independent systems (GPS and radar). The radar system is capable of precisely localizing and tracking objects, while the described system is able to identify registered objects. This paper contains a description of the subsystems of a portable/mobile electronic device. The fusion of information from the proposed system (rough location and identification) with the precise location obtained from short-range radar is intended to reduce the number of false alerts in the surveillance system.

Considerations for trustworthy cross-border interoperability of digital identity systems in developing countries

AbstractIn developing nations, the implementation of Foundational Identity Systems (FIDS) has optimised service delivery and inclusive economic growth. Cross-border e-government will gain traction as developing countries increasingly look to identity federation and trustworthy interoperability through FIDS for the identification and authentication of identity holders. Despite this potential, the interoperability of FIDS in the African identity ecosystem has not been well-studied. Among the difficulties in this situation are the intricate internal political dynamics that have led to weak institutions, suggesting that FIDS could be used for political purposes; additionally, citizens’ or identity holders’ habitual low trust in the government raises concerns about data security and privacy protection. Similarly, vendor lock-in, cross-system compatibility, and ambiguous legislative rules for data exchange are other concerns. Interoperability is fundamentally necessary as a precondition for e-government services and serves as the foundation for the best possible service delivery in the areas of social security, education, and finance, as well as gender equality as demonstrated by the European Union (EU). Moreover, the integration of cross-border FIDS and an ecosystem of effective data governance will be created by unified data sharing via an interoperable identity system. Thus, in this study, we point to the challenges, opportunities, and requirements for cross-border interoperability in an African setting. Furthermore, we investigated current interoperability solutions such as the EU’s eIDAS and Estonian X-Road and proposed an approach for scoping requirements to achieve a fully functional interoperable identity ecosystem in the African setting. Our findings show that interoperability in the African identity ecosystem is essential for expanding the scope of e-government throughout the continent and for bolstering the smooth authentication and verification of identity holders for inclusive economic growth.

Household Food Expenditure and Stunting of Children under Five Years Old in Food Secure Area

Background: Indonesia retains a high stunting prevalence which varies between regions. The government preliminarily has specific and sensitive nutrition programs. However, few studies have investigated the prevalence of stunting in food-secure areas and its association with the nutrition program. Therefore, the current research aims to analyze the prevalence of stunting and its relationship with socioeconomic factors and nutritional intervention programs received by children or their families in food-secure areas. Methods: This cross-sectional study included 140 children under five and their parents/ caregivers. Chi-square and logistic regression were applied to examine the correlation of stunting prevalence with other variables. Results: The prevalence of stunting was 38.6%. The factors that were significantly correlated with stunting prevalence were maternal education level (P=0.01), household food expenditure in the animal-based foods group (P=0.009), ready-to-eat foods (P=0.002), total food expenditure (P=0.003), and information from health workers about the use of iodized salt (P=0.033). Conclusions: High stunting prevalence is present in food-secure areas. Therefore, increasing maternal education and improving household food access, particularly for animal protein and ready-to-eat food, can be potential strategies to reduce stunting problems in food-secure areas.

Current Situation of Chinese Academia’s Study on the Korean Peninsula -Focusing on the Analysis of Political, Diplomatic, and Security Areas-

Current Situation of Chinese Academia’s Study on the Korean Peninsula -Focusing on the Analysis of Political, Diplomatic, and Security Areas-

Frame-Based Change Detection Using Histogram and Threshold to Separate Moving Objects from Dynamic Background

Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.

An Attacker-Defender Game Model with Constrained Strategies.

Recently, research interest in the field of infrastructure attack and defense scenarios has increased. Numerous methods have been proposed for studying strategy interactions that combine complex network theory and game theory. However, the unavoidable effect of constrained strategies in complex situations has not been considered in previous studies. This study introduces a novel approach to analyzing these interactions by including the effects of constrained strategies, a factor often neglected in traditional analyses. First, we introduce the rule of constraints on strategies, which depends on the average distance between selected nodes. As the average distance increases, the probability of choosing the corresponding strategy decreases. Second, we establish an attacker-defender game model with constrained strategies based on the above rule and using information theory to evaluate the uncertainty of these strategies. Finally, we present a method for solving this problem and conduct experiments based on a target network. The results highlight the unique characteristics of the Nash equilibrium when setting constraints, as these constraints influence decision makers' Nash equilibria. When considering the constrained strategies, both the attacker and the defender tend to select strategies with lower average distances. The effect of the constraints on their strategies becomes less apparent as the number of attackable or defendable nodes increases. This research advances the field by introducing a novel framework for examining strategic interactions in infrastructure defense and attack scenarios. By incorporating strategy constraints, our work offers a new perspective on the critical area of infrastructure security.

Big Data Technology Usage in Electric Transportation Industry

In the context of critical challenges related to global warming and the necessity of reducing carbon footprint, the electric car sector is experiencing significant growth. This progress inevitably leads to the need for expansion and modernization of the charging station infrastructure. This article conducts a detailed analysis of how big data processing technologies can contribute to the optimization of this infrastructure’s use, the efficiency of charging stations, and the development of personalized services for electric vehicle users. Strategies for solving current problems, particularly in the areas of data security and standardization, are discussed, along with the impact of big data on the formation of new commercial models in the electric transport sector. Special attention is given to the analysis of existing scientific works and publications, which reveal a noticeable deficit of research focused on adapting big data technologies to specific regional conditions and analyzing the behavioral models of electric vehicle consumers. The article identifies key directions for future research aimed at exploring the potential of big data for the intelligent optimization of electric vehicle transport, particularly in areas such as demand forecasting, effective management of charging stations, development of new user services, and integration with broader urban transport management systems. Additionally, the article highlights challenges related to ensuring the confidentiality and security of collected data, the need to integrate diverse data and systems, and the current demand for qualified professionals in the field of big data analysis. The final section of the article focuses on the prospects of using big data in electric transport, their potential contribution to the development of smart city concepts, infrastructure improvement, and enhancing the quality of services for end consumers. Recommendations are provided for key stakeholders in the industry, with the aim of facilitating the adoption of strategic decisions that would take into account future opportunities and challenges. An analytical review of current literature sources and online publications is included, emphasizing the innovative nature of the research conducted.

Counter-Terrorism and Human Rights at the UN Security Council: Blurring Boundaries in a Social Space

Abstract How do we study the UN Security Council, a bastion of sovereign nation-state politics, from the perspective of “outsiders” such as UN special rapporteurs? This article reimagines the relationship between security and human rights at the UN through a social space approach. By challenging institutional and geographical boundaries between the Security Council in New York and the Human Rights Council in Geneva, I follow actors in a social space in which transversal lines connecting security and human rights become visible. I uncover a social space that is animated by actors, their relations and social positions relative to each other as well as connections between institutions, geographical locations, practical competencies, and material infrastructures. On this basis, I theorize four distinct boundary-blurring practices of UN special rapporteurs: between the issue areas of human rights and security, between the geographical locations of New York and Geneva, between institutions such as the Security Council, Human Rights Council and the OHCHR, and between the domains of politics and law. While these practices help them enter into the social space of the Security Council in New York, special rapporteurs need to pay “entry costs” by accepting the basic premises of the counter-terrorism architecture in return for recognition as valid actors in this architecture. Taking this viewpoint from the outside, I argue, illuminates the extension of the Security Council beyond its institutional confines and uncovers “the human-rightisation” of global security policy.

Analysis of the Impact of Blockchain Technology Adoption on Operational Efficiency and Consumer Trust in Digital Business

This research intends to assess the influence of blockchain technology adoption on operational efficiency and consumer trust in digital enterprises. Blockchain technology, with its decentralized, transparent and safe properties, is predicted to have a favorable impact on several elements of business operations and boost consumer trust. The research method employed is a quantitative approach by collecting data through surveys and interviews with organizations that have incorporated blockchain technology. Data analysis was carried out using descriptive and inferential statistical techniques to test the stated hypotheses. The research results demonstrate that the deployment of blockchain technology greatly boosts operational efficiency, particularly in terms of reduced transaction costs, increased processing speed, and reduced operational errors. Apart from that, customer confidence has also improved dramatically, notably in areas of openness, security and data protection. These findings demonstrate that blockchain technology not only contributes to enhancing the operational performance of enterprises, but also boosting the trust relationship between firms and consumers. The conclusion of this study is that the implementation of blockchain technology has a considerable positive influence on operational efficiency and consumer trust in digital enterprises. Therefore, organizations working in the digital ecosystem are recommended to explore integrating blockchain technology as a strategy to boost competitiveness and consumer trust.

Патриотическое воспитание как фактор укрепления национальной безопасности России

Introduction: the article demonstrates the necessity of revising approaches to education and upbringing in the context of Russia's geopolitical transformation, both internal and external. Materials and Methods: regulatory acts, including the Constitution of the Russian Federation, scientific sources were the material basis for the study; the author used universal and specific legal methods such as comparative law method. Results: the author considers political and legal formation of national priorities in upbringing and education considering economic and social development of the country. Discussion and Conclusions: nowadays Russia rethinks moral and patriotic education for future generations in view of the challenges and threats that the country experienced in recent years. Since 1990, gained experience of liberal reform in upbringing and education caused the need to transform the ideological basis of this strategically vital line in the domestic policy defining areas of national security.

Strengthening human‐centered face recognition in law enforcement: Combining the Zurich face cognition test with the holistic cognitive interview

AbstractIn the area of security, human cognition remains essential for face recognition despite advancements in technology. Law enforcement agencies (LEAs) are interested in harnessing these abilities, as recognizing people is a fundamental aspect of their work. We conducted two studies to support integrating human face recognition skills into police work. In study 1, we developed the Zurich Face Cognition Test (ZFCT), a self‐assessment tool that reliably measures the face cognition abilities of police officers with authentic police material. Our approach is complementary to the identification of super‐recognizers. In study 2, we evaluated the Holistic Cognitive Interview (HCI), a method successfully applied in the UK to recognize facial composites better. Our results indicate that the HCI provides an effective strategy for police officers to memorize images of unfamiliar faces more effectively, for example, for better recognition of wanted or missing persons.

Wpływ wojny w Ukrainie na rozwój polityki bezpieczeństwa i obrony Unii Europejskiej

THE IMPACT OF RUSSIA’S 2022 INVASION OF UKRAINE ON EU SECURITY AND DEFENCE POLICY In recent years, the European Union has continuously expanded its role in the area of security and defense policy. This process gained momentum following Russia’s full-scale invasion of Ukraine in February 2022. New decisions and initiatives on common defense were developed due to the effects of the war, which changed the dynamics of interaction between institutions and member states. The analysis highlights how the EU is using the opportunities created by crises to strategically expand its security policy mandate. It also examined how the war in Ukraine led to the establishment of new security and defense initiatives, which affected its geopolitical position.

DX프로세스 환경에서의 중소제조기업 보안영역 수립과 보안 가이드라인에 대한 연구

As digital transformation (DX) develops, various security threats occur, mainly in the manufacturing industry. This study considers the characteristics of small and medium-sized manufacturing companies in the DX environment. Moreover, the security threats to small and medium-sized manufacturing companies are derived, security areas are established from technical and management perspectives, and minimal guidelines for each area are proposed. Based on these results, small and medium-sized manufacturing companies can establish security policies that are tailored to the size of the company, assets, importance of work, and business areas that require digital transformation.