Vulnerability Of Systems Research Articles

Security Infrastructure Service and Information Security Management Capability Audit to Improve System Security in Preventing Cyber Attacks using COBIT 2019

Cyber-attacks have become a serious concern in recent years, as hackers can attack systems, databases, and even steal personal data from a particular organization's database and sell it on the dark web. The individual identity data will be used to carry out various financially profitable activities such as online fraud, selling data containing detailed account information, and asking for ransom from data owners. The failure of an organization to protect data assets from cyber-attacks stems from several internal factors such as the vulnerability of the information security system it has, the less than optimal awareness of users in the organization of the importance of maintaining safe behavior in cyberspace, and routine processes related to information security that are missed. COBIT 2019 can be used as an audit framework to assess the level of maturity of the governance. Network infrastructure services in an organization can be measured in terms of the level of capability in terms of the application of technology assets and their configuration using the DSS05 and APO13 domains. This study aims to provide guidelines in assessing system security infrastructure in IT governance by assessing areas that are still not comply with the framework used, and providing recommendations for improving these inconsistencies so that the level of infrastructure capability will be maximized then.

Fraud App Detection using Machine Learning Algorithms

Abstract - The increasing number of mobile applications has resulted in a rise in malicious software, including fraud apps that take advantage of user permissions and system vulnerabilities to compromise sensitive personal and financial data. This paper introduces a comprehensive fraud detection system that leverages machine learning techniques to classify mobile applications as either benign or malicious. The system is implemented as a web-based platform using Flask, enabling users to upload, analyse, and classify APK (Android Package) files efficiently. Important features, such as application permissions and metadata (including app name, target SDK version, and file size), are extracted from APK files and transformed into feature vectors for classification by two machine learning models: an Artificial Neural Network (ANN) and a Support Vector Classifier (SVC). The ANN model achieves a classification accuracy of 92.26%, while the SVC model reaches an accuracy of 89%. To improve model performance further, a Genetic Algorithm (GA) is used for feature selection, which reduces the number of features and enhances both the computational efficiency and predictive accuracy of the models. The system offers an intuitive user interface that allows users to interact with the detection models, preview datasets, select classification algorithms, and view in-depth results, including safety recommendations for uploaded APK files. Additionally, the system provides visualizations of performance metrics and highlights the importance of specific features, improving the interpretability and transparency of the decision-making process.

Emergency Care for Refugee Patients at Suceava Hospital, Romania: Challenges and Insights from the First Year of the Russian-Ukrainian Conflict

Background: The ongoing military conflict in Ukraine has had a devastating impact on children’s health, exposing them to a range of illnesses. The aim of this study was to analyze the most common medical conditions among Ukrainian children since the beginning of the conflict, with a focus on identifying and understanding these problems in a wartime setting. Method: To assess the health status of affected children, we collected data from 422 pediatric patients who presented to the emergency department. The analysis included reviewing medical records, documenting the nature of illness, treatments administered, and the need for hospitalization. Results: Preliminary results indicate that interstitial pneumonia, contusions, gastroenterocolitis, and traumatic brain injury were the most common conditions. Of the 422 children studied, 80% received appropriate care without hospitalization, while 20% were admitted for further evaluation. Conclusions: Interstitial pneumonia was diagnosed in 23% of patients, highlighting the vulnerability of the respiratory system under conflict conditions. Contusions were predominant among musculoskeletal injuries, accounting for 81% of cases, and gastroenterocolitis was diagnosed in 46% of patients, reflecting the impact of poor living conditions.

Mitigation strategies can alleviate power system vulnerability to climate change and extreme weather: a case study on the Italian grid

Abstract This study explores compounding impacts of climate change on power system’s load and generation, emphasising the need to integrate adaptation and mitigation strategies into investment planning. We combine existing and novel empirical evidence to model impacts on: (i) air-conditioning demand; (ii) thermal power outages; (iii) hydro-power generation shortages. Using a power dispatch and capacity expansion model, we analyse the Italian power system’s response to these climate impacts in 2030, integrating mitigation targets and optimising for cost-efficiency at an hourly resolution. We outline different meteorological scenarios to explore the impacts of both average climatic changes and the intensification of extreme weather events. We find that addressing extreme weather in power system planning will require an extra 5–8 GW of photovoltaic (PV) capacity, on top of the 50 GW of the additional solar PV capacity required by the mitigation target alone. Despite the higher initial investments, we find that the adoption of renewable technologies, especially PV, alleviates the power system’s vulnerability to climate change and extreme weather events. In fact, renewable energy sources are generally less vulnerable to the impacts of climate change, such as rising temperatures and shifting precipitation patterns, compared to thermal power and hydropower generation. Furthermore, enhancing short-term storage with lithium-ion batteries is crucial to counterbalance the reduced availability of dispatchable hydro generation.

Asymmetrical vulnerability of heterogeneous multi-agent systems under false-data injection attacks

This paper investigates the vulnerability of heterogeneous multi-agent systems (MASs) in face of perfect false-data injection (FDI) attacks that stealthily destabilize the synchronization processes of agents. In contrast to homogeneous dynamics, heterogeneous dynamics can be asymmetrically worsened by attackers, which is a greater challenge for MAS security. First of all, the existence conditions of perfect FDI attacks in different agents are established based on the spectral radius of heterogeneous system matrices. Then, it is proven that the attack targets against communication links are determined by the characteristic space of different agents. Since the attack properties including the attack existence and targets are different in each agent, heterogeneous MASs have the asymmetrical vulnerability under perfect FDI attacks. Finally, a sufficient condition and a necessary condition are obtained to achieve perfect FDI attacks with minimum attack targets. A numerical simulation of heterogeneous MASs is presented to demonstrate the effectiveness of perfect FDI attacks.

Recovery from spreading depolarization is slowed by aging and accelerated by antioxidant treatment in locusts.

Spreading depolarization (SD) temporarily shuts down neural processing in mammals and insects. Age is a critical factor for predicting the consequences of SD in humans. We investigated the effect of aging in an insect model of SD and explored the contribution of oxidative stress. Aging slowed the recovery of intact locusts from asphyxia. We monitored SD by recording the DC potential across the blood-brain barrier in response to bath application of the Na+/K+-ATPase inhibitor, ouabain. Ouabain induced changes to the DC potential that could be separated into two distinct components: a slow, permanent negative shift, like the negative ultraslow potential recorded in mammals and human patients, and rapid, reversible negative DC shifts (SD events). Aging had no effect on the slow shift but increased the duration of SD events. This was accompanied by a decrease in the rate of recovery of DC potential at the end of the SD event. An attempt to generate oxidative stress using rotenone was unsuccessful, but pretreatment with the antioxidant, N-acetylcysteine amide, had opposite effects to those of aging, reducing duration, and increasing rate of recovery, suggesting that it prevented oxidative damage occurring during the ouabain treatment. The antioxidant also reduced the rate of the slow negative shift. We propose that the aging locust nervous system is more vulnerable to stress due to a prior accumulation of oxidative damage. Our findings strengthen the notion that insects provide useful models for the investigation of cellular and molecular mechanisms underlying SD in mammals.NEW & NOTEWORTHY Anoxia and similar energetic crises trigger a shutdown of central neural processing in a process of spreading depolarization (SD) that is generally pathological in mammals and protective in insects. We show that older animals are slower to recover from SD in an insect model. Moreover, preventing oxidative stress with an antioxidant speeds recovery. These findings demonstrate the role of oxidative stress in contributing to the vulnerability of the aging insect central nervous system (CNS) in energetic emergencies.

Blockchain-enhanced Cloud Security Frameworks: Addressing Human-network Vulnerabilities in Public and Private Sector Systems

Blockchain-enhanced Cloud Security Frameworks: Addressing Human-network Vulnerabilities in Public and Private Sector Systems

A conceptual framework for identifying and managing system vulnerabilities for diversion of controlled substances in healthcare.

Diversion or theft of controlled substances is a recognized problem affecting healthcare systems globally. The purpose of this study was to develop a framework for identifying and characterizing system factors leading to vulnerabilities for diversion within hospitals. We applied a qualitative framework method, which involved 1) compiling a list of critical diversion vulnerabilities through observations and proactive risk analyses in the inpatient pharmacy, emergency department and intensive care unit of two Canadian hospitals; 2) coding the vulnerabilities into deductively and inductively derived themes and subthemes; and 3) building a conceptual framework. Our framework for diversion demonstrates how mitigating downstream diversion outcomes (e.g., harms to patients, healthcare workers, and institutions) requires the redesign of upstream system factors associated with pilfering and forgery processes. We identified 20 subthemes associated with the following five overarching themes of system factors contributing to diversion risk: task (e.g., variation in how work was done or lack of verification), person (e.g., use of insider knowledge or collaboration among staff), tools/technologies (e.g., limitations of electronic systems to identify discrepancies), organization (e.g., cultural/behavioural norms or hospital policies for controlled substance management), and internal environment (e.g., layout of the space). The Diversion Framework is a conceptual model developed for use by practitioners, researchers, and policy makers to identify system factors and analyze medication-use processes that may be vulnerable to diversion. This in turn can inform safeguards to prevent harm to patients, healthcare workers and the institution.

Behind Closed Doors: Understanding the Layers of Illicit Wealth in Pakistan’s Money Laundering Web and Tracing the Socio-Economic Fallouts

This research investigates the clandestine realm of money laundering, with a particular emphasis on the complex operations that are involved inside the financial trajectory of Pakistan. The purpose of this article is to shed light on the diverse nature of the illegal acquisition of riches by investigating the mysterious systems and networks that support activities related to money laundering. This study attempts to provide a thorough understanding of the processes that are driving illegal financial flows in Pakistan by gaining an understanding of the layers of secrecy that constitute the situation. Furthermore, it investigates the far-reaching socioeconomic ramifications of money laundering, including the negative effects that it has on government, economic development, and social cohesion. Through the use of empirical analysis and case studies, the research sheds light on the issues that money laundering poses to the integrity and stability of Pakistan's financial system. The purpose of this study is to contribute to the ongoing conversation on the fight against financial crimes and the enhancement of anti-money laundering measures by tracing the socio-economic fallout. In light of these findings, it is imperative that systemic vulnerabilities be addressed and regulatory frameworks be strengthened in order to reduce the negative effects that money laundering has on Pakistan's economy and society.

The Big Catch-up: Addressing Zero-Dose Children as a Surrogate of Vaccination Disruptions During Public Health Emergencies: A review of literature

The COVID-19 pandemic triggered an unprecedented backslide in global immunization programs, increasing the number of zero-dose children-those who have not received any vaccinations—from 13.3 million in 2019 to 18.1 million in 2021. This surge poses a significant threat to public health, especially in low- and middle-income countries (LMICs), where healthcare systems are already fragile. This scoping review focused on the impact of the pandemic on childhood immunization, with a focus on zero-dose children, and to identify effective interventions for rebuilding resilient immunization systems. Data from WHO, UNICEF, and Gavi were comprehensively reviewed. The IRMMA (Identify, Reach, Monitor, Measure, Advocate) framework was used to structure the analysis of evidence-based interventions across diverse settings. Consolidated findings show that in 2022, 20.5 million children missed one or more vaccines, with 14.3 million classified as zero-dose children. Despite improvements from 2021, these numbers remain higher than pre-pandemic levels. Countries such as Nigeria (2.3 million zero-dose children), India (1.1 million), and Ethiopia (1.1 million) are most affected. Our review highlights the importance of strengthening health systems and leveraging innovative strategies such as drone delivery and digital health platforms for reaching zero-dose children. To ensure sustainability, policy interventions must focus on integrating immunization efforts into national healthcare frameworks. This includes prioritizing workforce development, enhancing supply chain management, and fostering partnerships with community leaders to rebuild trust and address vaccine hesitancy. Specific interventions, such as deploying mobile vaccination units, implementing culturally tailored health messaging, and utilizing real-time monitoring technologies, are recommended to target under-reached populations. The pandemic has exacerbated existing vulnerabilities in immunization systems but coordinated global efforts, like the "Big Catch-Up" campaign, offer a pathway to recovery and long-term sustainability. This scoping review underscores the urgent need for robust, context-specific policies and targeted interventions to bridge the immunization gap and protect vulnerable populations from vaccine-preventable diseases.

Advancing national security and economic prosperity through resilient and technology-driven supply chains

In today’s globally interconnected world, resilient and technology-driven supply chains are pivotal to ensuring national security, economic stability, and competitive growth. The complexities of modern trade, coupled with geopolitical tensions, natural disasters, and cybersecurity threats, have exposed vulnerabilities in traditional supply chain systems. These disruptions not only threaten critical infrastructure but also undermine economic prosperity by increasing costs and reducing efficiency. Advanced technologies such as blockchain, artificial intelligence (AI), and the Internet of Things (IoT) offer transformative solutions to these challenges. Blockchain enhances transparency and security by providing immutable records of transactions, ensuring accountability across supply chain networks. AI optimizes operations through predictive analytics, improving demand forecasting, inventory management, and risk assessment. Meanwhile, IoT enables real-time monitoring, allowing stakeholders to track assets, environmental conditions, and logistics with unprecedented precision. Together, these technologies empower supply chains to adapt dynamically, fostering resilience against disruptions. Beyond operational improvements, technology-driven supply chains hold strategic importance for national security. Secure and transparent supply chains mitigate risks associated with critical resources, such as semiconductors and energy, while fostering domestic manufacturing capabilities. Economically, these innovations enhance efficiency, create jobs, and enable businesses to remain globally competitive. This paper explores the intersection of technology and supply chain resilience, highlighting their contributions to national security, economic prosperity, and sustainable development. It emphasizes the need for robust policy frameworks, interdisciplinary collaboration, and scalable solutions to ensure the future of secure and efficient global trade systems.

Development of superposition-based quantum key distribution protocol in decentralized full mesh networks

The object of this research is the security of communication networks, particularly in decentralized, multi-user environments where robust data protection and integrity are critical. The issue under discussion is the rising vulnerability of conventional cryptography systems resulting from ever complex cyberattacks and the expected risks presented by quantum computing possibilities. The development of a QKD protocol employing quantum superposition to improve data security and resilience against both present and future quantum-based cyber-attacks is demonstrated by the achieved results of this work. Achieving scalability and autonomous eavesdropping detection, this protocol lets several communication nodes securely exchange randomly produced keys without centralized management. A quick analysis of the results reveals that main elements influencing the great durability, security, and adaptability of the protocol are quantum superposition and its distributed character. Without centralized authority, the characteristics of the obtained results – especially the use of optical components, detectors, and quantum sources in conjunction with classical communication channels – solve the problem of ensuring data confidentiality and integrity in a multi-user environment. This protocol's practical reach covers safe communication applications in both public and private sectors, therefore addressing situations calling for strong data protection against modern cyberattacks. Conditions for practical application include settings like government, financial, or health-related interactions when safe information flow is crucial. This QKD system offers a future-ready security solution for high-stakes environments and represents notable advancement toward protecting data from quantum and conventional attacks

Declining resilience of forest carbon sinks linked to increased atmospheric water deficit during droughts in the Northern Hemisphere

Abstract Droughts have posed intense threats to the forest carbon sink (i.e. net ecosystem productivity, NEP), potentially elevating the risk of forest degradation and challenging the achievement of climatic and ecological goals. While global forest NEP endured, the resilience of NEP served as the ability of ecosystems to withstand and recover from perturbations and the underlying maintenance mechanisms during droughts remain unclear. Here, we explored the responses of NEP resilience, quantified by the lag-1 temporal autocorrelation coefficient (TAC) of two consecutive time series, to droughts based on 87 drought events across 45 forest sites with flux and meteorological observations in the Northern Hemisphere. Furthermore, an interpretable machine learning algorithm was utilized to disentangle the synergistic effects of environmental and biotic factors on TAC, achieving a mean coefficient of determination of 0.87 for drought events with significantly increasing TAC and 0.91 for other drought events. Here, we found that the increase in NEP resilience could alleviate the negative effects of droughts, in contrast to a 2.5 times increase in the probability of NEP decline events associated with decreased NEP resilience. However, NEP resilience declined with the rise of drought intensification. The reduced reference canopy conductance (G cref) was the primary constraint on NEP resilience maintenance, contributing 48% to the total influence of biotic factors. In addition, high vapor pressure deficit (VPD) exacerbated the negative effects of soil moisture deficit, jointly leading to the decline in NEP resilience. Specifically, elevated VPD during droughts significantly reduced G cref, indicating the vulnerability of tree hydraulic systems to compound stress. Overall, our study emphasizes the potential risks of the compound soil and atmospheric water deficit on forest NEP resilience and carbon sink across the Northern Hemisphere in the future.

An Optimized Transmission Mechanism for Mitigating Jamming Attacks in Multi-Hop Wireless Networks

Aim: To address the vulnerability of Multi-Hop Wireless Network Systems (MHWNs) to jamming attacks and propose an effective solution to maintain communication integrity and Quality of Service (QoS). Background: In MHWNs, the open-access nature makes them susceptible to jamming attacks, which disrupt communication by interfering with authenticated nodes in the wireless medium. Existing methods primarily focus on tracking and countering jammers but lack effectiveness in preventing communication disruptions. Objective: The objective of this study is to introduce a novel algorithm, Optimized Transmission Mechanism (OTM), to mitigate the impact of jamming attacks on MHWNs. OTM aims to optimize node handover and packet routing to bypass jammed areas, ensuring uninterrupted packet transmission and preserving QoS. Methods: The proposed OTM algorithm determines the optimal transmission route based on radio transmitter location and connection quality. It prioritizes routes with the highest connection quality to maintain QoS even in jammed conditions. Additionally, it incorporates mechanisms for packet redirection away from jammed areas to ensure successful transmission. Results: Evaluation of the Extended Optimized Transmission Mechanism (EOTM) demonstrates significant improvements in packet delivery performance compared to existing algorithms. The enhanced algorithm effectively mitigates the impact of jamming attacks, ensuring reliable communication and preserving QoS in MHWNs. Conclusion: The proposed OTM algorithm presents a promising approach to counter-jamming attacks in MHWNs by dynamically routing packets to avoid jammed areas and maintain communication integrity. The results highlight the effectiveness of EOTM in improving packet delivery performance and ensuring uninterrupted communication in the face of jamming threats.

Ecological Indicators and Estimators of Fish and Crustacean Diversity in the Yucatan Peninsula

Biodiversity patterns provide insights into the conservation value of ecosystems and also aid in an understanding of some research priorities. This research paper presents an exhaustive inventory of crustaceans and fish species from the Yucatan Peninsula’s epicontinental, underground, and anchialine aquatic systems. Using records spanning from 1936 to 2024, this study analyzed over 2600 entries across 670 aquatic systems, including cenotes, flooded cave lakes, springs, and wetlands. A total of 329 species were recorded, comprising 117 fish and 212 crustacean species. The richness and endemism of these species were assessed through a completeness analysis, utilizing non-parametric models (Chao 2, Jackknife 1, Bootstrap) to estimate potential species richness. Notably, the region exhibits high endemism, especially among crustaceans, with up to 50 species and 2 endemic families being unique to the Yucatan Peninsula. This study underscores the importance of the eastern YP for crustaceans and the central YP for fish, highlighting areas critical for conservation. These findings emphasize the need for further exploration, as the diversity of aquatic species remains incompletely understood. This comprehensive synthesis aims to inform future conservation strategies, environmental management, and regional planning efforts, particularly highlighting the vulnerability of these unique aquatic systems to environmental degradation.

Component‐level seismic fragility database of suspended piping systems in buildings

AbstractNonstructural components (NSCs) contribute about 80%–90% of the construction investment in a modern public building. The post‐earthquake safety and normal operation of NSCs are necessary to achieve performance‐based design and resilient buildings. The piping system is one of the most essential nonstructural systems to preserve the post‐earthquake functionality of public buildings. To accurately evaluate the seismic performance and vulnerability of piping systems in buildings, a component‐level seismic fragility database is urgently to be developed. System composition, failure modes of piping systems, and induced consequences during previous earthquakes are introduced first in this article. Then a concise description of component‐level fragility methodology suggested by the Applied Technology Council is presented. Seismic fragility database of piping components including pipes, piping joints, and seismic braces through quasi‐static tests are developed based on the fragility analysis method. Experimental results from available literature are summarized and presented in the form of seismic fragility curves. Specific hysteretic curves of these components are also presented, which are used for the calibration of numerical models. In addition, the future research directions on the seismic fragility of piping components are summarized and prospected. The developed component‐level seismic fragility database can be used to help understand the seismic performance and post‐earthquake damage states of the piping system. Seismic performance assessment and seismic fragility analysis of modern piping systems can be conducted using the developed database and numerical simulation method.

Vulnerabilities of European telecommunication systems and the EU’s concerns about ETSI’s legitimacy – a proposal for value-based standardization

Vulnerabilities of European telecommunication systems and the EU’s concerns about ETSI’s legitimacy – a proposal for value-based standardization

Review of Fuzz Testing to Find System Vulnerabilities

Review of Fuzz Testing to Find System Vulnerabilities

Measuring the Systemic Risk of Clean Energy Markets Based on the Dynamic Factor Copula Model

This study is based on the stock returns of 11 subindustry markets in the international clean energy market from 2010 to 2024 and constructs a skewed t distribution dynamic factor copula model. The time-varying load factor is used to characterize the correlation between a single subindustry market and the entire system, and the joint probability of distress is calculated as a measure of the overall level of systemic risk. Two indicators, Systemic Vulnerability Degree and Systemic Importance Degree, are introduced to evaluate the vulnerability of a single subindustry market in systemic risk and its contribution to systemic risk. A conditional risk-spillover index is constructed to measure the risk-spillover level between subindustry markets. This method fully considers the individual differences and inherent correlations of the international clean energy market subsectors, as well as the fat tail and asymmetry of returns, thus capturing more information and more timely information. This study found that the correlation between subindustry markets changes over time, and during the crisis, the market correlation shows a significant upward trend. In the measurement of the overall level of systemic risk, the joint probability of distress can identify the changes in systemic risk in the international clean energy market. The systemic risk of the international clean energy market presents the characteristics of rapid and multiple outbreaks, and the joint default risk probability of the whole system can exceed 0.6. The outbreak of systemic risk is closely related to a series of major international events, showing a strong correlation. In addition, the systemic vulnerability analysis found that the biofuel market has the lowest systemic vulnerability, and the advanced materials market has the highest vulnerability. The energy efficiency market is considered to be the most important market in the system. The advanced materials market and renewable energy market play a dominant role in the risk contribution to other markets, while the geothermal market, solar market, and wind energy market are net risk overflow parties in the tail risk impact, and the developer market and fuel cell market are net risk receivers. This study provides a theoretical basis for systemic risk management and ensuring the stability of the international clean energy market.

Macroeconomic and energy impacts of Russia’s invasion of Ukraine: A comparative analysis across countries

The 2022 Russian invasion of Ukraine has triggered profound economic and energy-related consequences, reshaped global priorities, and exposed systemic vulnerabilities. The current study aimed to examine pre- and post-invasion trends in key economic and energy indicators for a diverse set of countries: Ukraine and Russia as directly involved parties; the European Union, the United States, and the United Kingdom as supporters of Ukraine; and China, India, and Türkiye as neutral actors maintaining economic ties with Russia. Using structural time series analysis over the period 2000–2023, the analysis maps economic booms and busts by identifying cycle deviations through a Hodrick-Prescott filter. The findings reveal significant variations in the conflict’s impact, highlighting disruptions in GDP growth, energy systems, and trade dynamics across regions. The study underscores how the war has accelerated energy transitions, redefined global economic resilience, and reshaped international economic and political relationships.