Vulnerability Of Systems Research Articles

Availability of essential medicines during the COVID-19 pandemic: A qualitative study examining experiences and level of preparedness in Kenya.

This study examines the impact of the COVID-19 pandemic on the availability of essential medicines in Kenya and suggests actionable measures to enhance the country's preparedness for future pandemics. Utilising a cross-sectional qualitative design, the research combines a systematic review of the literature and 20 key informant interviews to provide a comprehensive analysis. The initial response to the pandemic involved resource reallocation, disrupting the procurement of essential medicines at national and county levels. Inefficiencies in these systems resulted in shortages and wastages of crucial medicines, exposing vulnerabilities in the health system. Furthermore, the study reveals regulatory policy weaknesses in Kenya, such as an inadequate legal framework for domestic pharmaceutical manufacturing and conflicting policies hindering medicine availability. The study recommends a multifaceted policy approach to ensure essential medicine availability during crises. Key recommendations include strengthening financial systems through increased government investments and innovative funding mechanisms, implementing price regulation policies, and enhancing the resilience of supply chain and procurement systems. Collaboration among various supply systems is essential to prevent stock-outs. Strengthening legislation and regulatory policies, increasing domestic pharmaceutical manufacturing capacity, and investing in health information systems are vital for sustained self-sufficiency and efficient service delivery. These comprehensive measures are essential to promote essential medicine availability, safeguard public health, and enhance resilience during crises.

AAPM task group report 288: Recommendations for guiding radiotherapy event narratives.

Incident reporting and learning systems provide an opportunity to identify systemic vulnerabilities that contribute to incidents and potentially degrade quality. The narrative of an incident is intended to provide a clear, easy to understand description of an incident. Unclear, incomplete or poorly organized narratives compromise the ability to learn from them. This report provides guidance for drafting effective narratives, with particular attention to the use of narratives in incident reporting and learning systems (IRLS). Examples are given that compare effective and less than effective narratives. This report is mostly directed to organizations that maintain IRLS, but also may be helpful for individuals who desire to write a useful narrative for entry into such a system. Recommendations include the following: (1) Systems should allow a one- or two-sentence, free-text synopsis of an incident without guessing at causes; (2) Information included should form a sequence of events with chronology; and (3) Reporting and learning systems should consider using the headings suggested to guide the reporter through the narrative: (a) incident occurrences and actions by role; (b) prior circumstances and actions; (c) method by which the incident was identified; (d) equipment related details if relevant; (e) recovery actions by role; (f) relevant time span between responses; (g) and how individuals affected during or immediately after incident. When possible and appropriate, supplementary information including relevant data elements should be included using numerical scales or drop-down choices outside of the narrative. Information that should not be included in the narrative includes: (a) patient health information (PHI); (b) conjecture or blame; (c) jargon abbreviations or details without specifying their significance; (d) causal analysis.

Blood-based frailty index in patients with acute ischemic stroke undergoing endovascular treatment.

Frailty is a syndrome depicting vulnerability of multiple physiological systems to stressors. Frailty measures, such as Hospital Frailty Risk Score (HFRS), can be used to identify frailty and predict outcome more reliably. Our aim was to analyse a blood-based frailty index (FI-B) at admission for prediction outcome of patients with acute ischemic stroke (AIS) undergoing endovascular treatment (EVT). We conducted a retrospective study of consecutive AIS patients undergoing EVT in a single tertiary centre during a period of five years. A set of eighteen blood parameters at admission were collected and nine of these were utilized to calculate FI-B. We analysed the relationship between FI-B and HFRS. We examined the baseline characteristics of the study population based on FI-B-tertiles. Multivariable regression models were employed to ascertain the association between FI-B and in-hospital mortality, 3-month mortality and 3-month functional outcome. The final study population comprised 489 patients, with a median age of 75.6 years, 49.5% of patients were male. The FI-B exhibited a weak positive correlation with HFRS (rho=0.113, p=0.016). Patients in higher FI-B-tertiles were older and more frequently presented with pre-stroke functional dependence and comorbidities. Moreover, an increasing FI-B was independently associated with increased likelihood of in-hospital mortality (adjusted odds ratio [aOR]=1.29, 95% confidence interval [95%CI]=1.14-1.47), 3-month mortality (aOR=1.26, 95%CI=1.11-1.43), and of increasing 3-month functional disability measured by utility-weighted modified Rankin Scale (common aOR=0.84, 95%CI=0.76-0.93). A frailty index based on blood values at admission was able to identify frailty in AIS patients undergoing EVT and was an independent predictor of short- and medium-term outcome after stroke.

Locus coeruleus integrity and neuropsychiatric symptoms in a cohort of early- and late-onset Alzheimer's disease.

Early-onset Alzheimer's disease (EOAD) shows a higher burden of neuropsychiatric symptoms than late-onset Alzheimer's disease (LOAD). We aim to determine the differences in the severity of neuropsychiatric symptoms and locus coeruleus (LC) integrity between EOAD and LOAD accounting for disease stage. One hundred four subjects with AD diagnosis and 32 healthy controls were included. Participants underwent magnetic resonance imaging (MRI) to measure LC integrity, measures of noradrenaline levels in cerebrospinal fluid (CSF) and Neuropsychiatric Inventory (NPI). We analyzed LC-noradrenaline measurements and clinical and Alzheimer's disease (AD) biomarker associations. EOAD showed higher NPI scores, lower LC integrity, and similar levels of CSF noradrenaline compared to LOAD. Notably, EOAD exhibited lower LC integrity independently of disease stage. LC integrity negatively correlated with neuropsychiatric symptoms. Noradrenaline levels were increased in AD correlating with AD biomarkers. Decreased LC integrity negatively contributes to neuropsychiatric symptoms. The higher LC degeneration in EOAD compared to LOAD could explain the more severe neuropsychiatric symptoms in EOAD. LC degeneration is greater in early-onset AD (EOAD) compared to late-onset AD. Tau-derived LC degeneration drives a higher severity of neuropsychiatric symptoms. EOAD harbors a more profound selective vulnerability of the LC system. LC degeneration is associated with an increase of cerebrospinal fluid noradrenaline levels in AD.

Recent advances in diagnosis of immune-mediated cerebellar ataxias: novel concepts and fundamental questions on autoimmune mechanisms.

Immune-mediated cerebellar ataxias (IMCAs) represent a group of disorders in which the immune system targets mainly the cerebellum and related structures. We address fundamental questions on the diagnosis and immunological pathogenesis of IMCAs, as illuminated by recent advances in the field. Various types of IMCAs have been identified, including post-infectious cerebellitis, Miller Fisher syndrome, gluten ataxia, paraneoplastic cerebellar degeneration (PCD), opsoclonus and myoclonus syndrome, and anti-GAD ataxia. In some cases, identification of several well-characterized autoantibodies points to a specific etiology in IMCAs and leads to a firm diagnosis. In other cases, various autoantibodies have been reported, but their interpretation requires a careful consideration. Indeed, some autoantibodies have only been documented in a limited number of cases and the causal relationship is not established. In order to facilitate an early treatment and prevent irreversible lesions, new entities have been defined in recent years, such as primary autoimmune cerebellar ataxia (PACA) and latent autoimmune cerebellar ataxia (LACA). PACA is characterized by autoimmune features which do not align with traditional etiologies, while LACA corresponds to a prodromal stage. LACA does not imply the initiation of an immunotherapy but requires a close follow-up. Concurrently, accumulation of clinical data has led to intriguing hypotheses regarding the mechanisms of autoimmunity, such as a pathogenesis of autoimmunity against synapses (synaptopathies), and the vulnerability of the entire nervous system when the immunity targets ion channels and astrocytes. The development of PCD in patients treated with immune-checkpoint inhibitors suggests that molecular mimicry specifically determines the direction of autoimmunity, and that the strength of this response is modulated by co-signaling molecules that either enhance or dampen signals from the antigen-specific T cell receptor.

Analisis Kerentanan Keamanan Website Menggunakan Metode PTES (Penetration Testing Execution And Standart)

With rapid advances in Information Technology (IT), the need for an IT-based learning framework and mechanism has become an unavoidable necessity. This requires solid security in a system, using the Penetration Testing Execution and Standard (PTES) method. This research method is quantitative and descriptive, used to illuminate website security and provide input for improvement. The research involved Tenable Nessus Professional tools that emit vulnerabilities, such as Browseable Web Directory and Potentially Clickjacking Web. The PTES stages covered include Planning, Data Collection, Scanning, Access Rights, Security, and Web Application Firewall (WAF) configuration. The hope is that this method will provide an in-depth understanding of potential threats and vulnerabilities in government information systems, as well as present solutions. The research results are expected to provide education and insight into website security. This allows related parties to take preventive and corrective steps, improve security, and protect the integrity and confidentiality of data entities. As a result, information systems are expected to be more secure and resistant to potential cyber threats.

Can a relational cross-scalar approach to management improve environmental disaster responses? A case study of an unprecedented flood in New South Wales, Australia

ABSTRACT Human societies face planetary crises of climate change, biodiversity loss and pollution. Conventional command-and-control approaches to manage these existential challenges have failed due to limited comprehension of relationships in social-ecological systems. To address this problem, we study the complex case of the disaster response to unprecedented floods in the Northern Rivers Region, New South Wales, Australia, in 2022. We apply a novel relational-systems model that identifies management structures, processes, functions and contents interacting at and across scales. The model helps identify the root causes in the inadequate disaster response that ensued in the Northern Rivers Region flooding. The root causes are a lack of systems-thinking competence, poor collaborative capacity, vulnerabilities in environmental management and deficient governance systems. The relational complexity concepts of self-organisation and socio-cultural organisation may further help explain variation in response to disasters in different socio-ecological contexts. Such understanding can inform individual and collective environmental action.

New Electric Power System Stability Evaluation Based on Game Theory Combination Weighting and Improved Cloud Model

The development of new electric power system is a requirement for China to realize its “carbon peaking and carbon neutrality goals”, so it is of great importance that we assess the stability of a new electric power system under certain conditions. Firstly, according to the factors affecting the stability of the new power system, the characteristics of the new electric power system are analyzed in depth, so as to establish a stability evaluation index system including four first-level indices of safety, adequacy, flexibility, and adaptability. Secondly, a stability evaluation model is proposed. Based on the game theory, the entropy weight method, criteria importance though intercrieria correlation (CRITIC) method, and coefficient of variation method are combined and assigned, and the cloud model is improved through the combination of weights, which is used for evaluating the stability of the new electric power system. Finally, the applicability of the proposed evaluation model is verified by an arithmetic example analysis, which can identify the vulnerability of the new electric power system and provide suggestions for improving its stability. The model can provide a theoretical basis for promoting energy transition and sustainable development.

Criticality assessment and cascading effects: impacts of COVID-19 disruptions in public transport on marginalized groups in Dortmund, Germany, São Paulo, Brazil, and Cape Town, South Africa

The COVID-19 pandemic has underscored the interconnectedness of critical infrastructure systems and their profound impact on marginalized communities. This study investigates the cascading effects of reduced mobility and infrastructure disruptions caused by COVID-19 response strategies on marginalized households across three diverse urban settings: Dortmund, São Paulo, and Cape Town. Employing a criticality assessment, we examine disruptions in healthcare, food and nutrition, social work, education, and childcare sectors, highlighting interdependencies and their implications for marginalized communities. Our findings reveal that disruptions in one sector, such as public transportation, can trigger adverse consequences across interconnected systems, amplifying vulnerabilities and exacerbating social inequalities. Furthermore, limited digital accessibility compounds these challenges, particularly for marginalized groups who may lack access to necessary technologies or digital literacy skills. Addressing these disparities in digital access is crucial for ensuring equitable access to essential services and support networks, especially in times of crisis. The study underscores the importance of mobility and accessibility in addressing systemic vulnerabilities and advocates for comprehensive resilience strategies that prioritize the needs of marginalized communities. Recommendations for policymakers, urban planners, and community stakeholders are provided to enhance infrastructure resilience and mitigate the indirect effects of disruptions on marginalized groups. The study contributes to a deeper understanding of cascading effects within critical infrastructure networks and informs future research and policy initiatives aimed at building resilient communities in an interconnected world.

Micro Knowledge as a Driver for Systemic Emergencies Management: The Case of Xylella in Italy

AbstractDuring emergency production systems, supply chain stakeholders’ interactions, media activities, government actions, community behaviors are stressed bringing, all, to a high-risk perception about safety. For agri-food products, it became in a variation of consumers’ purchasing behaviors, guided by uncertainty and influenced by trust. The extant knowledge about consumers’ willingness to buy for agri-food products in emergency condition does not provide evidences during a phytosanitary warning. The proposed study, considering the Xylella fastidiosa phytosanitary emergency as case study, aims to fulfill this gap analyzing the possible variations of consumers’ perception and willingness to buy of Apulian olive oil in the era of Xylella emergence by adopting a multi-perspective and systemic approach. For achieving this scope, the study follows a Process-Person-Context-Time perspective for conceiving a systemic psychological model based on the Bronfenbrenner ecological model. Seven hypotheses were tested through Structural Equation Modeling thanks to a survey in a representative sample of 779 Italian consumers. Results showed that Italian consumer’s willingness to buy the post-Xylella olive oil can fluctuate due to the hypothesized system vulnerability: family, friends, and colleague such as trust in farmers and the credibility of Italian food market are impactful; trust in processors, transporters, and government and media is not. The findings, from theoretical and sectorial perspectives, provide new knowledge on the topic, empirical evidences, and a multi-systemic model able to analyze consumers’ behaviors, understand and stimulate the search for new (or more appropriate) marketing and communication strategies to face Xylella serious economic shortages, and to act a requalification of territory at all.

ПРОАКТИВНОЕ МОДЕЛИРОВАНИЕ УТЕЧЕК ДАННЫХ ОГРАНИЧЕННОГО ДОСТУПА НА ОБЪЕКТАХ КРИТИЧЕСКОЙ ИНФОРМАЦИОННОЙ ИНФРАСТРУКТУРЫ (НА ПРИМЕРЕ ТРАНСПОРТНОЙ ОТРАСЛИ)

The article presents a comprehensive methodology for predicting data breaches and assessing the potential risks of harmful effects on critical information infrastructure, using the example of the transport industry. Statistical data on the number of restricted access data leaks in Russia from 2013 to 2022 are analyzed. Within the study, several numerical forecasting methods are compared: linear regression, moving average smoothing, and exponential smoothing. Linear regression was found to be the most accurate method for predicting restricted access data leaks in the transport sector for 2024 to 2028. Additionally, a cognitive model is proposed that allows for assessing the likelihood of data breaches and their potential consequences, considering factors such as attack vectors, system vulnerabilities, user behavior, and implemented security measures. The combined approach, which combines numerical methods and cognitive modeling, provides a comprehensive view of cybersecurity risks. This allows for more accurate predictions and better-informed decisions. The study's results emphasize the importance of considering both technical and human aspects in improving cybersecurity, and offer recommendations for future research that could refine the cognitive model by involving experts from not only the technical field, but also the economic and legal domains.

Nucleation phenomena and extreme vulnerability of spatial k-core systems

K-core percolation is a fundamental dynamical process in complex networks with applications that span numerous real-world systems. Earlier studies focus primarily on random networks without spatial constraints and reveal intriguing mixed-order transitions. However, real-world systems, ranging from transportation and communication networks to complex brain networks, are not random but are spatially embedded. Here, we study k-core percolation on two-dimensional spatially embedded networks and show that, in contrast to regular percolation, the length of connections can control the transition type, leading to four different types of phase transitions associated with interesting phenomena and a rich phase diagram. A key finding is the existence of a metastable phase where microscopic localized damage, independent of system size, can cause a macroscopic phase transition, a result which cannot be achieved in traditional percolation. In this case, local failures spontaneously propagate the damage radially until the system collapses, a phenomenon analogous to the nucleation process.

Securing demand–response in smart grids against false pricing attacks

Two-way communication systems in smart grids help to engage consumers in demand–response programs, which can bring many benefits but also make smart grids vulnerable to cyber attacks. In this paper, a cyber attack which aims to disturb the demand–response process by injecting false electricity price signals is considered. A real-time pricing model where the operator has incomplete knowledge of the private demand–response behaviors of the customers is proposed. The vulnerability of the power system to false pricing attacks is analyzed by a Markov decision process, and the dynamic interaction between the attacker and the defender is modeled as a zero-sum Markov game where neither player has full information of the game model. For the solution of the Markov game, a model-free multi-agent reinforcement learning method is proposed to find the Nash Equilibrium policies for both players. The proposed method is applied to the IEEE 34 Node Test Feeder, in which the effect of the defense on mitigating the impact of the attack is demonstrated and different policies of the players given various resources are analyzed. The results shows that the studied cyber attack can cause a maximum of 1.96% unsatisfied load and the proposed defense measure can reduce the unsatisfied load by 50%–70% compared with the cases without defense measures.

The Role of Machine Learning in Advanced Biometric Systems

Today, the significance of biometrics is more pronounced than ever in accurately allowing access to valuable resources, from personal devices to highly sensitive buildings, as well as classified information. Researchers are pushing forward toward devising robust biometric systems with higher accuracy, fewer false positives and false negatives, and better performance. On the other hand, machine learning (ML) has been shown to play a key role in improving such systems. By constantly learning and adapting to users’ changing biometric patterns, ML algorithms can improve accuracy and performance over time. The integration of ML algorithms with biometrics, however, introduces vulnerabilities in such systems. This article investigates the new issues of concern that come about because of the adoption of ML methods in biometric systems. Specifically, techniques to breach biometric systems, namely, data poisoning, model inversion, bias injection, and deepfakes, are discussed. Here, the methodology consisted of conducting a detailed review of the literature in which ML techniques have been adopted in biometrics. In this study, we included all works that have successfully applied ML and reported favorable results after this adoption. These articles not only reported improved numerical results but also provided sound technical justification for this improvement. There were many isolated, unsupported, and unjustified works about the major advantages of ML techniques in improving security, which were excluded from this review. Though briefly mentioned, we did not touch upon encryption/decryption aspects, and, accordingly, cybersecurity was excluded from this study. At the end, recommendations are made to build stronger and more secure systems that benefit from ML adoption while closing the door to adversarial attacks.

‘A storm is coming:' The New York Times coverage of the COVID-19 pandemic in American prisons

ABSTRACT In this research, we analyzed the content of 171 articles published between March and August 2020 in the New York Times (NYT) on COVID-19 in American correctional institutions. We observed that the NYT coverage decreased significantly over 6 months. Our analysis uncovered 8 themes within two broader frames: institutional and systemic inequity. Although the themes are not mutually exclusive, we argue that ‘Responding to COVID-19,’ ‘A storm is Coming,' ‘Collective Experience,' and ‘Critiquing Prison Conditions' are within the institutional framing. ‘Redefining Public Safety,' ‘Categorizing Prisoners,' ‘Doing Injustice,' and ‘Making it as a Celebrity' are the themes that highlight systemic inequity, systematic inequalities, and vulnerabilities of incarcerated people, especially minorities. Although this study is not a test of any theory, the themes are viewed via the lenses of conflict theory. Our analysis showed also that American prisons faced two simultaneous crises: mass incarceration and the COVID-19 pandemic, and that mass incarceration is not strictly a criminal justice problem, but also a public health issue. We found that the policies introduced during pandemic in the American correctional institutions were not only inadequate, but also revealed significant systemic inequalities.

Land use and land cover patterns as a reflection of subsurface architecture groundwater quality in a large urban center (Varanasi) in the Ganges river basin, India

Varanasi is an exponentially developing city in the Himalayan-sourced Ganges river basin. To understand the sustainable groundwater-sourced drinking water in Varanasi, it is essential to study the land use-land cover that reflects the surface geomorphology vis-a-vis sub-surface geology, and influence groundwater conditions. We incorporate lithological and groundwater data obtained from an extensive network of boreholes in and around the city at 110 sites, reaching a maximum depth of 100 m below ground level (bgl). The unconsolidated subsurface are primarily composed of sand, silt, clay, and gravel where, silty clay layer. Groundwater quality and stresses were determined through multi-dimensional hydrogeological approaches. The data were analyzed through multivariate statistics (Principal Component Analyses to identify the governing factor influencing the broad hydrogeochemistry. PC1 for urban areas has higher loading values for Fe, Cl− compared to Semi-urban areas highlighting contamination by municipal wastewater. PC2 for urban areas shows higher loading values for Mg2+ and HCO3− compared to semi-urban areas. Due to heavy urbanization in Varanasi, the aquifer suffers substantial groundwater abstraction during particular times of the day compared to the agricultural lands. An increase of about 9% in built-up areas within a span of 10 years (2012–2022) poses a threat to the aquifer system of our study area, jeopardizing access to sustainable drinking water. With the expansion of urbanization and unregulated groundwater extraction, the vulnerability of the aquifer system will probably increase in the foreseeable future. Implementation of sustainable water management policies, engaging all economic sectors of the population in Varanasi, can expedite the process and safeguard the aquifer from attaining its emerging vulnerability. Thus, comprehending evolving groundwater risks through non-invasive methods like that discussed in the present study, holds significant promise for effectively targeting safe groundwater availability in future.

Integrated management of safety and security barriers in chemical plants to cope with emerging cyber-physical attack risks under uncertainties

Chemical facilities face threats from accidental and intentional events, including the rising concern of cyber-physical (C2P) attacks in the digitized industrial control system era. Addressing major accident risks from safety hazards and C2P attacks requires an immediate unified framework for safety and security barrier management. This study presents a systematic risk-based approach to integrate conventional safety risks with emerging C2P attack risks. Adverse scenarios are identified, integrated into an attack-tree-bow-tie diagram, and modelled using a Bayesian network (BN). A vulnerability assessment model is developed to quantify industrial control system vulnerability to C2P attacks, considering uncertainties in attackers' knowledge levels. Monte Carlo simulations are used to handle uncertainty propagation in risk assessment, allowing the use of probability distributions for BN root nodes. Sensitivity analysis identifies critical factors/events, guiding the proposal of candidate strategies for barrier improvements. Combining cost-effectiveness analysis with a risk matrix yields the optimal strategy for safety and security barrier enhancements based on risk estimations. A hypothetical case study demonstrates the proposed approach's effectiveness in integrated safety and security barrier management, considering security vulnerability patching and safety barrier maintenance scheduling from a cost-effective perspective.

Adults With Spina Bifida Fare Worse than Young Adults: A Systemic Vulnerability in Urinary Tract Infection-Related Hospital Care.

We aim to estimate the odds of urinary tract infection (UTI)-related hospital care in spina bifida (SB) patients age 18 to 25 years as compared with patients with SB in adolescence (11-17 years) or adulthood (26-35 years). We hypothesize that patients with SB in the typical transitional age, 18 to 25 years, will have higher odds of UTI-related hospital care as compared to adolescent SB patients or adult SB patients. Using Cerner Real World Data, we performed a retrospective cohort analysis comparing SB patients to an age- and gender-matched controls. SB cases between 2015 and 2021 were identified and compared in 3 cohorts: 11 to 17 years (adolescents), 18 to 25 years (young adults [YA]), and 26 to 35 years (adults). Logistic regression analysis was used to characterize the odds of healthcare utilization. Of the 5497 patients with SB and 77,466 controls identified, 1839 SB patients (34%) and 3275 of controls (4.2%) had at least 1 UTI encounter. UTI-related encounters as a proportion of all encounters significantly increased with age in SB patients (adolescents 8%, YA 12%, adult 15%, P < .0001). Adjusting for race, sex, insurance and comorbidities, the odds of a UTI-related encounter in YA with SB was significantly higher than for adolescents with SB (adolescent OR = 0.65, 95% CI: 0.57-0.75, P < .001). YA had lower odds of a UTI-related encounter as compared with adults with SB (adult OR = 1.31, 95% CI: 1.16-1.49, P < .001). Young adults with SB have higher odds of UTI-related hospital care than adolescents, but lower odds of UTI-related hospital care when compared with adults.

A robust multi-key authority system for privacy-preserving distribution and access control of healthcare data

Innovation in medical technology and communication has rapidly empowered the development of smart healthcare devices. This has led to privacy breaches, threats and vulnerabilities to sensitive patient data that result in unwanted or targeted advertising. Previous research has focused on protecting access to sensitive patient data from unauthorized entities, especially by defining roles of healthcare entities in the overall system with their access privileges. However, such efforts need to be further robust due to the involvement of a single key authority that may lead to a critical point of failure. In this paper, this vulnerability has been addressed by developing a novel approach to crucially increase the number of key authorities using homomorphic encryption. The proposed approach ensures genuine access to the verified entity by forming a subsystem of t key authorities from a total of n authorities (t<n). This creates rigorous challenge to a malicious attacker, obfuscating the selection and functioning of key access packets in a multi-key authority setup. The results of the proposed approach achieve medical data confidentiality, entity authentication, and strategic data sharing. The security of the proposed approach is assessed for different vulnerabilities of the overall system using a challenge–response game model. Moreover, the proposed approach is found to be better and secure as compared to existing schemes.

Harnessing the power of blockchain to strengthen cybersecurity measures: a review

As the digital environment continues to evolve with the increasing frequency and complexity of cybersecurity threats, there is growing interest in using blockchain (BC) technology. BC is a technology with desirable properties such as decentralization, integrity, and transparency. The decentralized nature of BC eliminates single points of failure, reducing the vulnerability of critical systems to targeted attacks. The complex and rapidly evolving nature of cyber threats requires an earlier and adaptive approach. This review paper examined several papers collected from official websites. Focusing on using BC technology to improve cybersecurity, the main keywords of the review paper were BC technology, supply chain management, proof of work, and proof of stake. This review paper aims to investigate the security components through a threat assessment that compares the security of BC in different classes and real attack environments. It highlights the potential of BC to strengthen cybersecurity measures, citing unique features. The review paper also points out that there is a lack of focus on addressing security challenges related to computer data and digital systems and calling for a deeper discussion on problem-solving.