Security Demands Research Articles

Utilizing method of plant growth regulators induction in processing of polyploidization—A perspective crop development

Nowadays, it seems like human beings are worried about how the world will meet its food security demand urgently when they have faced on rapidly increasing population and combat climate change. Scientists and researchers are indispensably investigating to enhance food sources such developing novel cops with high yield and good quality and even coping with the adverse environment in terms of biotic and abiotic stresses. Thus, there is one valuable method it is believed that should be developed further. In fact, it is believed that human beings should continue using it as soon as possible because it can provide the world with a source of food. Polyploidization introduced by plant growth regulator induction is a good method because it is safety and easy to develop new crops with potential agronomic traits, these polyploidy plants are rare aneuploid and it contains intriguing characteristics of polyploidy plants in adapting to ecological variability. This review sheds light on 1) summarizing molecular mechanism of plant growth regulator induction for plant ploidy manipulation; 2) achieving of polyploidization through plant growth regulator induction; 3) enumerating the perspectives of polyploidization in crop development to cope with climate change. Although the role of phytohormones is underestimated, the effectiveness on physiological level of plants to make polyploidy plants is worth considering and the effects and bio-safety of that on human are also concerned.

CORPORATE SOCIAL RESPONSIBILITY DISCLOSURE AND COST OF EQUITY EVIDENCE FROM PUBLIC LISTED COMPANIES IN MALAYSIA

Corporate social responsibility (CSR) has been rolled out in recent years as it has become vital owing to the massive growth of financial institutions, mutual funds, online resources, and other publications. CSR disclosure could reduce the cost of equity. The study's main objective is to investigate the CSR disclosure by companies listed in Malaysia towards the cost of equity. This study is based on three hundred four (304) samples of Malaysian listed companies from 2013 to 2014. The data of the samples were mainly collected from annual reports, except for financial data which were collected from DataStream. The result revealed that the CSR disclosure in the annual report could reduce the company's cost of equity by reducing information asymmetry, reducing agency costs, and reducing companies' risk. The result also shows that liquidity has a significant negative relationship with the cost of equity. The higher information disclosure enhances stock market liquidity, thus, reducing the cost of equity through the reduction of risk as well increasing demand for a company's securities. The size, liquidity, and growth have a significant relationship with the cost of equity.

Tackling African swine fever in India

Abstract Globally, African swine fever (ASF) is the most feared swine viral disease, associated with a mortality rate of up to 100%. More than half of the world’s swine population is located in Asia. ASF outbreaks in Asia have a significant impact on the global pig industry. Pig industry’s economic losses have been huge because of ASF outbreaks. Swine husbandry in India is in a flourishing phase to meet food security demands, but the losses associated with ASF greatly hamper its expansion. ASF in India can be controlled and eradicated through strict biosecurity measures and vaccination. Development of penside point-of-care (POC) rapid diagnostics and effective indigenous vaccines are prerequisites to tackle ASF in India. Sensitization of veterinary professionals, researchers, and pig farmers about disease pathogenesis, transmission, and impact are crucial part of ASF control. This review presents the status of ASF in India in comparison to other parts of the world, and current approaches in India to deal with ASF. Further roadmap to combat this calamitous swine infection in India.

IWRAM: A hybrid model for irrigation water demand forecasting to quantify the impacts of climate change

The phenomenon of climate change exerts a substantial influence on the water consumption patterns of agricultural crops, thereby affecting the overall demand for irrigation water and regional water security. The quantitative assessment of future changes in irrigation water requirements has great importance for long-term water resource planning and the water-energy-food-ecosystem nexus. This work employed a comprehensive approach (IWRAM) by integrating many models and techniques, including a global climate model (CanESM2), a statistical downscaling model (SDSM), a bias correction technique (QTM), a temperature-based crop phenology method (GDD), and deep learning technology (LSTM), in order to assess the potential impact of climate change on irrigation water demand. Therein, the QTM is utilized for the purpose of bias correction for the CanESM2-SDSMed daily precipitation data. Additionally, the LSTM is implemented to forecast ETo using the CanESM2-SDSMed daily temperature data. The findings from the case study conducted in the Jinghuiqu irrigation area (JIA) indicate that the application of bias correction techniques resulted in notable enhancements in the frequency distribution of predicted precipitation data. Consequently, this led to a more coherent relationship between historical observed data and anticipated future data, aligning them more closely with natural patterns. The deep learning technique exhibited a strong degree of concordance, suggesting its exceptional capacity for modeling daily reference evapotranspiration. By using the IWRAM model, relatively accurate predictions were made for future precipitation, temperature, crop evapotranspiration, and effective precipitation. Consequently, an estimation was made regarding the anticipated need for irrigation water in JIA. These results highlighted that JIA total irrigation water demand (or net irrigation water demand) will increase by 121 mm (net irrigation water: 189 mm) and 119 mm (net irrigation water: 187 mm) in the year 2050 under RCP 2.6 and 8.5 scenarios, respectively. Climate change could potentially affect the seasonal distribution of precipitation. Therefore, it is crucial for the authorities in JIA to not only take into account the overall irrigation water requirement but also give priority to the water requirements of each stage of crop growth.

RETRACTED ARTICLE: AI-enhanced security demand and routing management for MANETs with optical technologies

RETRACTED ARTICLE: AI-enhanced security demand and routing management for MANETs with optical technologies

Effectiveness of DNA barcoding, SCOT markers and phytochemical characterization in biodiversity assessment of some Zea mays hybrids

Because of the rapid fluctuation in world's climate, politics, and economy, maize outputs must be increased to meet food security demands. Due to the importance of the genetic materials under study as a source of quality traits and genetic variability, this study was designed to examine the effectiveness and strength of assessing biodiversity in some maize hybrids using barcodes and molecular SCoTs markers in addition to phytochemical characterization. Using matK and rbcL sequences, pairwise distances were obtained and assessed. The hybrids under study were distributed into different groups based on the matK and rbcL sequences. The 12 SCoT primers amplified 155 amplicons with an average of 12.92 bands per primer, of which 63 monomorphic bands (MB) (40.65 %) and 92 polymorphic band (PB) (59.35 %). Additionally, the number of unique bands was six bands. The SCoT-6 primer produced three bands individually, while the primers SCoT-2, SCoT-3, SCoT-4, and SCoT-7 produced one band each. Hybrids S.C. 10, S.C. 128, S.C. 130, S.C. 131, S.C. 132 and TWC. 324 were more influenced by some primary constituents and bioactive secondary compounds such as moisture content (%), crude fiber, total carbohydrates, total sugars, soluble carbohydrates, non-reducing sugars, phenolics compounds, and tannins. The hybrids S.C. 168, S.C. 176, S.C. 178, TWC. 360, TWC. 368 and TWC. 321 were more influenced by the SCoT molecular markers. The results of genetic variation between the studied hybrids could be considered a potentially source of genetic information in developing future breeding programs.

Balancing quality with quantity: A case study of UK bread wheat

Societal Impact StatementIncreasing crop productivity is often proposed as a key goal for meeting the food security demands of a growing global population. However, achieving high crop yields alone without meeting end‐use quality requirements is counter to this objective and can lead to negative environmental and sustainability issues. High yielding feed wheat crops in the United Kingdom are a typical example of this. The historical context of UK agricultural industrialisation, developments in plant breeding and wheat end‐use processing are examined. We then outline how employing innovations in plant breeding methods offer the potential to redress the balance between wheat quantity and quality.SummaryBread wheat (Triticum aestivum L.) has historically been an important crop for many human civilisations. Today, variability in wheat supply and trade has a large influence on global economies and food security. The United Kingdom is an example of an industrialised country that achieves high wheat yields through intensive cropping systems and a favourable climate. However, only a minority of the wheat grain produced is of suitable end‐use quality for modern bread baking methods and most wheat produced is fed to livestock. A large agricultural land area and input use dedicated to producing grain for animal rather than human food has wide‐ranging negative impacts for environmental sustainability and domestic food production. Here we present an historical perspective of agricultural and economic changes that have resulted in UK production primarily focussing on wheat quantity over quality. Agricultural intensification, liberalisation of free trade in agricultural commodities, innovations in the milling and baking sector, developments in scientific understanding of genetics and plant breeding, and geopolitical changes have all played a role. We propose that wheat breeding plays a crucial role in influencing these issues and although wheat breeders in the United Kingdom have historically applied the most‐up‐to‐date scientific advances, recent advances in genomics tools and quantitative genetics present a unique opportunity for breeders to redress the balance between quantity and quality.

The impact of the COVID-19 epidemic on agricultural production strategy from the perspective of loss aversion

Agricultural products have the characteristics of high perishability, short life cycles, and low salvage, and agricultural production is easily affected by uncontrollable natural conditions. Therefore, farmers will face great risk when making agricultural production decisions. In addition, farmers have a high demand for basic income security, so they are typically loss-averse decision-makers. Simultaneously, the impact of the COVID-19 epidemic has undoubtedly increased their loss aversion. The piecewise utility function is an effective model for investigating decision-making with consideration of loss aversion, in which the loss aversion parameter will be adjusted by the epidemic to a certain degree. We innovatively involve the impact of COVID-19 epidemic by a quantitative correction factor in the loss-averse newsvendor model to deal with the decision-making problem of agricultural production and investigate the influences of the epidemic and farmers’ loss aversion degree on the optimal production quantity and profits as well as the relationship between the epidemic situation and loss aversion. Through model analysis and numerical experiments on a specific agricultural product by Matlab software, it is found that the effect caused by the epidemic and the increased level of loss aversion will reduce farmers’ production and income. Therefore, it is necessary to strengthen regular epidemic prevention and control and formulate corresponding support policies to stimulate farmers’ production motivation. Maintaining relative stability in the agricultural market demand can also alleviate the negative impact of the epidemic to a certain extent. Faced with the impact of the epidemic, farmers need to do their best to control agricultural production costs to relieve their economic pressure.

Applications, Restrictions, and Evaluation of Quantum Cryptography for Secure Unmanned Aerial Vehicle Communication

Because of the abrupt increase in demand for security, researchers have developed immediate safety solutions that outperform state-of-the-art solutions. Data security was first sought for during the Spartan period. These days, efforts are being made to broaden this area of study by challenging the status quo and creating novel algorithms that outperform their weaker predecessors. Unmanned aerial vehicles, or UAVs, are widely used in a variety of industries, including agriculture, the military, healthcare, monitoring and surveillance, and many more, because of their svelte designs and adaptable mobility. In this post, we go over the significance of drone technology as well as its growth and demand. The study also discusses the current state of security concerns in real-time settings and how quantum cryptography outperforms conventional methods in protecting data. This inspires us to offer an overview of quantum cryptography's significance, function, and advantages in protecting UAV communications that go beyond 5G networks. Additionally, a unique layered architectural approach based on quantum cryptography is suggested to ensure excellent data security and effective transmission. A case study on the Internet of Military Things' implementation in the battlefield is also included in this presentation. The latency, security, and dependability of the suggested case study system are taken into account while assessing its performance.

Analyze the Impact of the Digital RMB on International Payments and Financial Structure Based on Literature Review

With the development of network technology and digital economy, the demand for convenience, security, inclusiveness and privacy of retail payment is increasing. Central banks or monetary authorities in many countries and regions are actively exploring ways to digitize fiat money to meet this demand. The Chinese government has decided to introduce digital RMB as a digital form of legal tender to enhance the payment experience, strengthen financial supervision, promote economic transformation and financial technology innovation and application. The introduction of digital RMB helps to reduce the cost and risk of traditional cash flow, promote the upgrading of payment methods and the development of digital economy. Based on the comprehensive and systematic collection, collation and analysis of the relevant literature in the field of digital RMB, this paper explores the impact of digital RMB on international payment and financial structure. The study found that digital RMB has international security as a payment tool, which can promote cross-border transactions and change the global payment system. Digital RMB can enhance international financial security and affect the implementation of financial policies in various countries.

Управління діяльністю фахівців з кібербезпеки в умовах повномасштабного вторгнення

In this study dedicated to the management of cybersecurity professionals in the context of full-scale intrusion, significant aspects of this pressing issue have been examined. Drawing from an analysis of the content of cybersecurity professionals' activities and their core concepts, it has been identified that this field encompasses various facets requiring diverse skills and knowledge from these experts. Specifically, cybersecurity experts must possess technical expertise, understand threats and risks, detect and thwart cyberattacks, and adhere to ethical and legal standards. Addi-tionally, the ability to communicate and collaborate within a team, while considering socio-cultural and legal peculiarities of the country they operate in, is vital. In the context of full-scale intrusion, such as russia's invasion of Ukraine in 2022, cybersecurity professionals face challenges of extraor-dinary complexity. They must respond to aggressive cyberattacks targeting various sectors, includ-ing governmental structures, critical infrastructure, media, and the information space. Simultane-ously, they must consider ethical aspects and responsibly engage with other entities and organiza-tions to ensure collective cyber defense. This research underscores the importance of adopting a comprehensive approach to manag-ing cybersecurity professionals in times of intrusion. To achieve this, it is essential to provide train-ing and continuous skill enhancement, establish effective mechanisms for detecting and responding to cyber aggression, and strengthen international cooperation in the field of cybersecurity. Through these measures, cybersecurity professionals will have the capability to effectively safeguard the in-terests of their organizations and nations amidst heightened cyber threats, ensuring the security, privacy, and rights of users. Such an approach contributes to creating a more resilient and secure in-formation environment, a critical factor in the modern world. Furthermore, the article presents a comparative analysis of soft skills and transferable skills for cybersecurity professionals, highlighting key abilities and qualities crucial in this field. This analysis helps develop more effective strategies for training and developing cybersecurity experts, enhancing their professional competence to meet contemporary security demands. This analysis also promotes the improvement of managing cybersecurity professionals in the context of large-scale in-trusion, emphasizing the importance of combining technical and interpersonal skills to ensure the reliability and effectiveness of cybersecurity.

Robust transformer-based anomaly detection for nuclear power data using maximum correntropy criterion

Due to increasing operational security demands, digital and intelligent condition monitoring of nuclear power plants is becoming more significant. However, establishing an accurate and effective anomaly detection model is still challenging. This is mainly because of data characteristics of nuclear power data, including the lack of clear class labels combined with frequent interference from outliers and anomalies. In this paper, we introduce a Transformer-based unsupervised model for anomaly detection of nuclear power data, a modified loss function based on the maximum correntropy criterion (MCC) is applied in the model training to improve the robustness. Experimental results on simulation datasets demonstrate that the proposed Trans-MCC model achieves equivalent or superior detection performance to the baseline models, and the use of the MCC loss function is proven can obviously alleviate the negative effect of outliers and anomalies in the training procedure, the F1 score is improved by up to 0.31 compared to Trans-MSE on a specific dataset. Further studies on genuine nuclear power data have verified the model's capability to detect anomalies at an earlier stage, which is significant to condition monitoring.

Timed Petri Nets for Modeling and Performance Evaluation of a Priority Queueing System

The application of queueing theory is very broad. Examples include electronic communication systems and devices. New technologies, electronic communication systems, and devices are used by many modern organizations. However, this implies certain requirements and risks. The requirements are, first and foremost, reliability, which accounts for the complexity and interdependence of the system. On the other hand, the stochastic characteristics and complexity of these systems introduce risks related to the demands of reliability control, transmission quality, availability, and security. The research conducted so far is concerned with relatively simple queueing models that require certain assumptions to be made about the stochastic nature of the event stream. This is because complex queueing systems are very difficult to analyze using analytical methods. Hence, this paper attempts to use timed Petri nets in the modeling and performance evaluation of queueing systems belonging to the PQS (Priority Queueing System) group. IntServ and DiffServ architectures are discussed, as well as queueing systems used in quality-of-service assurance. A weighted PQS that eliminates the possibility of blocking lower-priority traffic is investigated. Based on a Petri model, the performance characteristics of the studied system are obtained. The impact of data generation on the system performance was analyzed, showing that temporal Petri nets can be effectively used in the modeling and performance evaluation of PQS systems.

Challenges in nuclear energy adoption: Why nuclear energy newcomer countries put nuclear power programs on hold?

The pressing need to mitigate greenhouse gas emissions has stimulated a renewed interest in nuclear energy worldwide. However, while numerous countries have shown interest in nuclear power over the course of history, many of them have not continued their pursuit and chosen to defer or abandon their peaceful nuclear power projects. Scrapping a national nuclear power program after making initial efforts implies significant challenges in such a course or a waste of national resources. Therefore, this study aims to identify the crucial factors that influence a country's decision to terminate or hold off its peaceful nuclear power programs. Our empirical analyses demonstrate that major nuclear accidents and leadership changes are significant factors that lead countries to terminate or defer their nuclear power programs. Additionally, we highlight that domestic politics (democracy), lack of military alliance with major nuclear suppliers, low electricity demand, and national energy security environments (energy import, crude oil price) can hamper a country's possibility of regaining interest in a nuclear power program after it has been scrapped, suspended, or deferred. The findings of this study have significant implications for policymakers and stakeholders in the energy sector as they strive to balance the competing demands of energy security, and environmental sustainability.

An interpolation-based reversible data hiding scheme for internet of things applications

The exponential growth of the Internet of Things (IoT) has led to an increased demand for secure and efficient data transmission methods. However, there is a tradeoff in the image quality and hiding capacity in the data hiding methods. Therefore, the maximum amount of data that could be stored in the image media is a difficult challenge while maintaining the image quality. Thus, to make the balance between the quality of the images and the embedding capacity, a novel interpolation-based revisable data hiding (RDH) approach is developed for IoT applications. The proposed interpolation technique takes the average of the root value for the product of two neighboring original pixel values and the third original pixel value. And for the central pixel, it takes an average of two interpolated pixels. By doing so, most of the original pixels are considered and the calculated interpolated pixel is much enhanced as its average value. Furthermore, the data hiding is performed in two stages. In the first stage, RSA is performed on the secret message, and then embedding is done based on which intensity range group. The experimental results indicate that the proposed technique enhanced the embedding capacity by 17.58% and produced 7.80% higher PSNR values for the test images as compared to the baseline methods.

KBD-Share: Key Aggregation, Blockchain, and Differential Privacy based Secured Data Sharing for Multi-User Cloud Computing

In today's era of widespread cloud computing and data sharing, the demand for secure and privacy-preserving techniques to facilitate multi-user data sharing is rapidly increasing. However, traditional approaches struggle to effectively address the twin objectives of ensuring privacy protection while preserving the utility of shared data. This predicament holds immense significance due to the pivotal role data sharing plays in diverse domains and applications. However, it also brings about significant privacy vulnerabilities. Consequently, innovative approaches are imperative to achieve a harmonious equilibrium between the utility of shared data and the protection of privacy in scenarios involving multiple users. This paper presents KBD-Share, an innovative framework that addresses the intricacies of ensuring data security and privacy in the context of sharing data among multiple users in cloud computing environments. By seamlessly integrating key aggregation, blockchain technology, and differential privacy techniques, KBD-Share offers an efficient and robust solution to protect sensitive data while facilitating seamless sharing and utilization. Extensive experimental evaluations convincingly establish the superiority of KBD-Share in aspects of data privacy preservation and utility, outperforming existing approaches. This approach achieves the highest R2 value of 0.9969 exhibiting best data utility, essential for multi-user data sharing in diverse cloud computing applications.

A Novel Approach for Improving the Security of IoT–Medical Data Systems Using an Enhanced Dynamic Bayesian Network

IoT (Internet of Things) devices are increasingly being used in healthcare to collect and transmit patient data, which can improve patient outcomes and reduce costs. However, this also creates new challenges for data security and privacy. Thus, the major demand for secure and efficient data-sharing solutions has prompted significant attention due to the increasing volume of shared sensor data. Leveraging a data-fusion-based paradigm within the realm of IoT-protected healthcare systems enabled the collection and analysis of patient data from diverse sources, encompassing medical devices, electronic health records (EHRs), and wearables. This innovative approach holds the potential to yield immediate benefits in terms of enhancing patient care, including more precise diagnoses and treatment plans. It empowers healthcare professionals to devise personalized treatment regimens by amalgamating data from multiple origins. Moreover, it has the capacity to alleviate financial burdens, elevate healthcare outcomes, and augment patient satisfaction. Furthermore, this concept extends to fortifying patient records against unauthorized access and potential misuse. In this study, we propose a novel approach for secure transmission of healthcare data, amalgamating the improved context-aware data-fusion method with an emotional-intelligence-inspired enhanced dynamic Bayesian network (EDBN). The findings indicated that F1 score, accuracy, precision, recall, and ROC-AUC score using DCNN were 89.3%, 87.4%, 91.4%, 92.1%, and 0.56, respectively, which was second-highest to the proposed method. On the other hand, the F1 score, accuracy, precision, recall, and ROC-AUC scores of FRCNN and CNN were low in accuracy at 83.2% and 84.3%, respectively. Our experimental investigation demonstrated superior performance compared with existing methods, as evidenced by various performance metrics, including recall, precision, F measures, and accuracy.

Blockchain-Based Academic Identity and Transcript Management in University Enterprise Architecture

The present research examines the implementation of Blockchain-based Identity and Academic Transcript Management in a university's enterprise architecture. This research is motivated by the increasing demand for secure, transparent, and efficient student identity management and the need to store easily verifiable academic transcripts. Blockchain technology has been spotlighted because it provides security and data integrity solutions. This research aims to determine if integrating Blockchain into the University's Enterprise Architecture can improve the management of student identities and academic transcripts by reducing the risk of forgery and facilitating more dependable access for interested parties. Increased security and efficiency in managing student data are the practical implications of this research, which can help universities reduce the risk of data loss and increase stakeholder trust. This research method includes surveying various universities that have adopted Blockchain technology in their academic identity and transcript management. In addition, we will assess its technical implementation, evaluate its effect on efficiency, and conduct interviews with university personnel involved in the implementation process. This study's anticipated outcome is providing universities planning to adopt Blockchain technology for Enterprise Architecture with actionable guidance. This research will identify the benefits, challenges, and best practices of integrating Blockchain in academic identity and transcript management and lay the groundwork for further improvement of educational services in university settings.

민간조사제도에 대한 빅데이터 분석 연구

In this study, we would like to explore how the media means the private investigation system through “Big Cains,” a news big data analysis site. Therefore, it provided a big data system for the media and collected data from various media organizations to analyze media reports on private investigations through BigKinds, a news big data analysis system created as news content. In order to achieve the purpose of the research, the flow of keywords was identified by dividing them into 2000s, 2010s and 2020s and deriving and presenting the number of related articles every year during that period. As a result of this study, it was found that in the 2000s, the frequency of media reporting was low at a time when public interest in the private investigation system and various studies were not conducted in academia. Second, in the 2010s, there was a high topic rank on the private survey system compared to the 2000s, and various research and education were conducted in academia and industry related to government policies and private surveys. Third, the 2020s marked a high topic rank as related laws were revised, heralding a new change in the private investigation system. Therefore, it is hoped that the government will move in a direction that will greatly help the people's security demand by supplementing the protection of citizens' rights, minimizing conflicts between direct translations, and limitations of national security.

Global Health Security

To reduce the risk and effect of sudden incidents of public health that put people at risk across national and international boundaries, it is necessary to take both preventive and reactive measures. These measures are referred to as global health security. Discussions on health security in scientific gatherings have become more prevalent in recent years after the Covid pandemic. Health security is for the whole world, irrespective of age, race, gender, or financial stability. However, it has been noted that there are many different concepts of health security, that the whole purpose of this is to accommodate only the upper-class societies. The disturbed equilibrium of the microbial world due to rapid urbanization, population increase, environmental deterioration, and the improper use of antimicrobials makes people realize the importance of health security that requires a collaborative approach focused on preparedness for any future pandemics and equal access to health care products. 
 The covid-19 pandemic has had a great influence on people’s lives and their ability to think. Now the main race is not about defence systems; it has shifted towards more and better health security and the ability to deal with any future pandemics. The coronavirus outbreak was associated with severe acute respiratory syndrome, the Middle East respiratory syndrome coronavirus outbreak in 2012, the swine flu pandemic in 2009, and the West African Ebola virus disease epidemic in 2013–2016. All these epidemics are primarily caused by the significant travel of infected people across borders. This highlights the need for global health security, which helps coordinate surveillance and policymaking. This limits disease transmission and reduces the damage.
 While infectious diseases have no limits, inadequate health systems in poor nations make them worse and more out of control. Africa and other third-world states face many problems in securing global security. The spread of infectious diseases among susceptible areas is due to inadequate public healthcare fundings, vaccine coverage, poverty, armed conflict, and climate-related disasters, which damage developing countries. This only serves to increase susceptibility to the disease. The continuous transmission of polio and measles in different parts of Africa and Asia, as well as recent Ebola outbreaks in West Africa, highlights the need to overcome this in order to stop the spread of diseases to other areas. No nation can be completely protected from the spread of diseases due to a lack of social services and a strong health infrastructure; hence, global security demands global equality and progress towards health for everyone. 
 To advance global health security in all nations, there is a need for multi-stakeholders and governance, justifiable finance through the proposed pandemic funds, and common goods for health. Future outbreaks can be efficiently managed by funding basic healthcare and enhancing the response systems. Equity in pandemic preparedness and response measures depends on high-level political commitment and global leadership irrespective of colour and gender. False contradictions between countries can be dismissed by focused investments in strengthening health emergency infrastructure, particularly through primary healthcare, ensuring that the world is better prepared to handle complex public health emergencies.