Vulnerability Assessment Research Articles

Search for high-probability differential characteristics of the lightweight block cipher algorithm present with non-standard substitution blocks

The development of the Internet of Things and the associated devices has made it necessary to establish and implement encryption standards to ensure secure data transmission. These standards need to be comply with fundamental encryption principles and cater to devices with limited computational resources. As a result, lightweight cryptography has emerged as a distinct field within cryptography. The PRESENT block cipher algorithm is a lightweight encryption algorithm designed for deployment in resource-constrained devices. It requires comprehensive and ongoing vulnerability analysis against both known and novel cryptanalysis methods. This work extensively investigates the PRESENT block cipher algorithm, examining its components, operational principles, and key scheduling algorithm. This study analyses existing research on the algorithm with regards to contemporary cryptanalysis methods. Differential cryptanalysis was selected as the method of choice. The requirements for constructing S-boxes, as set forth by the algorithm developers, are reviewed. Two alternative S-boxes are formulated and presented based on these requirements. The paper presents a methodology for identifying high-probability differential characteristics for the PRESENT algorithm, using a substitute substitution block that differs from the one proposed by the developers. The research reports on the encryption algorithm PRESENT, using alternative substitution blocks, and evaluates its resistance to differential cryptanalysis. The text presents the results of applying the methodology for searching differential characteristics to the substituted blocks in the PRESENT algorithm. A comparative analysis is made between the results obtained through the differential characteristic search methodology for the PRESENT algorithm with alternative substitution blocks and the known results for this algorithm.

Water Supply Security—Risk Management Instruments in Water Supply Companies

Piped drinking water supplies are exposed to a range of threats. Changing hazard situations arise from climate change, digitisation, and changing conditions in the power supply, among other things. Risk and crisis management adapted to the hazard situation can increase the resilience of the piped drinking water supply. Analogous to the risk management system, this article describes a methodology that ranges from hazard analysis with the prioritisation of 57 individual hazards to vulnerability assessment with the help of balance sheet structure models (BSM) and the planning and implementation of measures to increase the resilience of the piped drinking water supply in a targeted manner. The work steps mentioned build on each other and were tested using the case study of a water supply company in Saxony (Germany). As a result, priority hazards are identified, the remaining supply periods and replacement and emergency water requirements are determined as part of the vulnerability assessment, and finally, planning principles for increasing resilience are documented. The methodology focuses primarily on practicable application by water supply companies.

Analysis of agricultural insurance vulnerability in the face of natural disasters: Insights from Iran

Agricultural insurance plays a crucial role in managing and mitigating damages from natural disasters, while also providing support to farmers through equitable risk distribution. This study focuses on identifying vulnerabilities of the Agricultural Insurance Fund (AIF) in Iran during natural disasters and proposing solutions for maintaining preparedness and adapting to new circumstances. Utilizing a qualitative approach, the research involved a three-stage classic Delphi technique with 24 experts in agricultural insurance which purposefully selected using snowball sampling. Three open-ended questions on AIF vulnerabilities in facing natural disasters, AIF's adaptive capacity, and forecasting strategic measures for the future, were provided in the first research round. After refining in subsequent rounds, a consensus was reached on 19 vulnerability points, 7 adaptive capacity factors, and 20 strategic actions. Key indicator of vulnerabilities includes the “weak financial capacity of the insurance fund”. “Designing an integrated agricultural insurance system” was the most crucial factor in enhancing AIF's adaptive capacity. Finally, the study proposes strategies like "strengthening financial capacity and ensuring sustainable credit resources," "developing capacities of the insurance system with location-based technologies," and "differentiating catastrophic damages in the insurance tariffing system" to address vulnerabilities and enhance agricultural insurance resilience.

Analysis of the hydrological disaster occurred in the state of Rio Grande do Sul, Brazil in September 2023: Vulnerabilities and risk management capabilities

Understanding disaster risk in all its dimensions is a priority on global agendas. This study developed an integrated analysis of flood risk drivers using a methodology based on meteorological and hydrological analyses, population vulnerability assessment, and municipal risk management capabilities from public data sources. Rio Grande do Sul, Brazil, was selected due to extreme rainfall that affected more than 400,000 people in September 2023. The results showed that a stationary frontal system caused unprecedented rain and floods between September 1 and 4, 2023. A quasi-stationary cold front from Argentina intensified precipitation, exacerbated by an upper-level low-pressure area. Attributed to the 2023 El Niño, these events resulted in heavy rainfall exceeding normal levels by 200–300 mm, leading to floods that affected 107 municipalities, resulting in 54 deaths and extensive property damage. The Caí and Taquari-Antas river basins were particularly affected, with river levels exceeding critical limits, causing severe floods and most deaths. Vulnerability was higher among populations of low socioeconomic status living in housing with precarious infrastructure, especially in small municipalities dependent on agriculture. The high vulnerability is due to the lack of public policies that improve socioeconomic conditions, such as social action policies for agricultural workers, combating educational delays, and improvements in household infrastructure. Furthermore, municipal administrations must invest in strengthening tools, actions, and policies focused on risk response and management, and promoting educational activities in civil protection and defense, with special attention to the elderly population.

Assessing metro network vulnerability with turn-back operations: A Monte Carlo method

Metro network disruptions caused by accidents or maintenance can significantly impact its serviceability. Traditionally, graph theory and complex network methods are utilized to examine topological properties by removing nodes, links, or entire lines. However, in practice, it is the turn-back operation that determines the service cancellations and the affected area. This study assesses metro network vulnerability by considering the turn-back section as the Vulnerability Analysis Unit (VAU). Indicators for evaluating topological accessibility and operational robustness are proposed to assess network performance under disruptions. Monte Carlo method is applied to generate scenarios, involving the removal of various combinations of VAUs. A case study is conducted on Shanghai Metro system. The results indicate that on average, when one VAU is damaged, the travel time will increase by 2.39 minutes and 1.75 % of passengers will move to other transport modes. The critical vulnerable sections are mainly located in radial lines connecting to the loop lines, while those located in or inside the loop line exhibit higher robustness.

Reversible Data Hiding in Encrypted Images Based on Preprocessing-Free Variable Threshold Secret Sharing

To solve the limitations of reversible data hiding in encrypted domains (RDH-ED) that cannot be applied to a distributed variable security environment, a novel RDH-ED scheme based on variable threshold image secret sharing (VTSIS) is proposed. Initially, a security vulnerability analysis of existing changing thresholds in a bivariate polynomial-based secret image sharing (TCSIS) method is conducted and validated through experiments. Subsequently, enhancements are made to the VTSIS scheme to rectify the identified security loopholes. During the image encryption process, additional data can be embedded into the redundancy of VTSIS, which results in a large embedding rate and high security. Finally, theoretical analysis and experimental proofs are carried out for the proposed scheme, and the results show that our scheme broadens the application scenarios of RDH-ED. Notably, the scheme eliminates the need for preprocessing and has the advantages of high security, a large embedding rate, and complete reversibility.

Consistent decrease in conifer embolism resistance from the stem apex to base resulting from axial trends in tracheid and pit traits.

Drought-induced embolism formation in conifers is associated with several tracheid and pit traits, which vary in parallel from stem apex to base. We tested whether this axial anatomical variability is associated with a progressive variation in embolism vulnerability along the stem from apex to base. We assessed the tracheid hydraulic diameter (Dh), mean pit membrane area (PMA) and the xylem pressure at 50% loss of conductivity (P50) on longitudinal stem segments extracted at different distances from the stem apex (DFA) in a Picea abies and an Abies alba tree. In both trees, Dh and PMA scaled with DFA 0.2. P50 varied for more than 3 MPa from the treetop to the stem base, according to a scaling of -P50 with DFA-0.2 . The largest Dh, PMA and P50 variation occurred for DFA<1.5 m. PMA and Dh scaled more than isometrically (exponent b=1.2). Pit traits vary proportionally with tracheid lumen diameter. Apex-to-base trends in tracheid and pit traits, along with variations in P50, suggest a strong structure-function relationship that is influenced by DFA. Although the effect of DFA on P50 has not been extensively explored previously, we propose that analyzing the relationship between P50 and DFA could be crucial for a comprehensive assessment of embolism vulnerability at the individual level.

Understanding flood risk in urban environments: spatial analysis of building vulnerability and hazard areas in the Lisbon metropolitan area

AbstractClimate change has brought about new risks while exacerbating existing ones, with floods now accounting for about 45% of global disasters. This trend indicates that the exposure to floods and resulting damages will continue to rise. This paper aims to contribute to the global efforts to enhance flood resilience in urban areas by introducing a physical vulnerability index for buildings in flood-prone urban areas and exploring its connection with flood hazard, as defined by the European Union Directive 2007/60/EC. An index-based methodology is proposed to assess the physical vulnerability of buildings to flooding, utilising the Portuguese Census and Georeferenced Buildings Database, collected on a nationwide scale. The physical vulnerability of buildings is evaluated in the context of the Lisbon metropolitan area (LMA) in Portugal, and the results are compared across different scales, contrasting flood hazard information for the entire LMA with the areas identified under the Flood Directive as having significant potential flood risk. Using cluster analysis, spatial patterns of flood risk are identified, highlighting areas where high flood depth and flood velocity overlap the high vulnerability of buildings. Lastly, potential adaptation paths are discussed, considering the diverse nature of the flood hazard and the lessons learnt from other flood events.

Assessment of vulnerability to flood risk in the Padma River Basin using hydro-morphometric modeling and flood susceptibility mapping.

An evaluation of flood vulnerability is needed to identify flood risk locations and determine mitigation methods. This research introduces an integrated method combining hydro-morphometric modeling and flood susceptibility mapping to assess Padma River Basin's flood risk. Flood zoning, flooding classes, and resource flood risk were explicitly analyzed in this river basin study. Flood risk was calculated using GIS-based hydro-morphometric modeling. Using Horton's and Strahler's methods, drainage density, stream density, and stream order of the Padma River Basin were determined. The Padma River Basin has five sub-basins: A, B, C, D, and E, with stream densities of 0.53km-2, 0.13km-2, 0.25km-2, 0.30km-2, and 0.28km-2 and drainage densities of 0.63km-1, 0.16km-1, 0.29km-1, 0.35km-1, and 0.33km-1, respectively. Sub-basin A is the most prone to floods due to its high stream and drainage density, whereas B and C are the least susceptible. This study used elevation, TWI, slope, precipitation, NDVI, distance from road, drainage density, distance from river, LU/LC, and soil type to create a flood vulnerability map incorporating GIS and AHP with pair-wise comparison matrix (PCM). The study's flood zoning shows that the northeastern part of this basin is more likely to flood than the southwestern part due to its elevation and high-order streams. Moderate River Flooding, the region's most hazardous flood class, covers 48.19% of the flooding area, including 1078.30 km2 of agricultural land, 94.86 km2 of bare soil, 486.39 km2 of settlements, 586.42 km2 of vegetation cover, and 39.34 km2 of water bodies. The developed hydro-morphometric model, the flood susceptibility map, and the analysis of this data may be utilized to offer long-term advance alarm insight into areas potentially to be invaded by a flood catastrophe, boosting hazard mitigation and planning.

Vulnerability to climate change of coastal mangrove-dependent communities in the Tana Delta, Kenya: a local perspective

Coastal mangrove-dependent communities face various risks due to climate change, thus rendering them vulnerable. This study explored the vulnerability of these communities in the Tana Delta in Kenya using an indicator-based vulnerability assessment framework to better understand their exposure, sensitivity and adaptive capacity. Data was collected through household surveys (n = 377), focus group discussions (FGDs), and key informant interviews (KIIs). The analysis revealed mean vulnerability indices at the sub-location level ranged from 0.850 for Kipini to − 0.913 for Kilelengwani and − 2.702 for Ozi. The statistically significant indicators of vulnerability were (i) exposure—high temperatures and rainfall changes; (ii) sensitivity—household numbers, head of household’s age, dependents’ education, and dependents’ employment; and (iii) adaptive capacity—ownership of assets, access to community infrastructure and services, condition/quality of houses, total income, and alternative sources of income. The findings highlight the need for adaptation strategies that ensure greater financial assets supported by education and skills enhancement to utilize existing opportunities. Attention to community infrastructure and services is crucial. Policy should focus on financial, physical, and human assets to reduce community vulnerability alongside the continued conservation and management of mangrove resources. The results will help policymakers in addressing the impacts of climate change and benefit households in the study area. These insights can be applied to regions with similar climate conditions and livelihood systems.

Risk factors for converting traditional wards to temporary intensive care units during the COVID-19 pandemic: Insights from nurses' perspectives.

The surge in critically ill COVID-19 patients caused a shortage of intensive care unit (ICU) beds. Some hospitals temporarily transformed general wards into ICUs to meet this pressing health care demand. This study aims to evaluate and analyse the risk factors in temporary ICU from the perspective of nurses. By identifying these factors, the goal is to provide actionable insights and recommendations for effectively establishing and managing temporary ICUs in similar crisis scenarios in the future. The study was conducted in China within a public hospital. Specifically, it focused on examining 62 nurses working in a temporary ICU that was converted from an infectious disease ward. The research utilized the Hazard Vulnerability Analysis (HVA) scoring method to identify potential threats, evaluate their probability, estimate their impact on specific organizations or regions and calculate the relative risk associated with such occurrences. Staff demonstrated the highest risk percentage (32.74%), with Stuff (16.11%), Space (15.19%) and System (11.30%) following suit. The most critical risk factors included insufficient knowledge and decision-making competence in critical care (56.14%), lacking decision-making abilities and skills in renal replacement therapy care (55.37%), inadequate decision-making capacity and relevant skills in respiratory support care (50.64%), limited decision-making capability in circulatory support care (45.73%) and unfamiliarity with work procedures or systems (42.09%). Urgent implementation of tailored training and support for temporary ICU nurses is paramount. Addressing capability and skill-related issues among these nurses supersedes resource availability, infrastructure, equipment and system considerations. Essential interventions must target challenges encompassing nurses' inability to perform critical treatment techniques autonomously and ensure standardized care. These measures are designed to heighten patient safety and elevate care quality during emergencies. These findings offer a viable avenue to mitigate potential moral distress, anxiety and depression among nurses, particularly those transitioning from non-critical care backgrounds. These nurses swiftly assimilate into temporary ICUs, and the study's insights offer practical guidance to alleviate their specific challenges. The study on risk factors for converting traditional wards into temporary ICU during the COVID-19 pandemic, especially from the perspective of nurses, provides crucial insights into the challenges and requirements for effectively establishing and managing these emergency settings. The findings highlight several key areas of concern and opportunities for improvement directly related to clinical practice, particularly in situations where there is a rapid need to adapt to increased demands for critical care. By addressing the identified risk factors through enhanced training, support systems, resource management, process improvements and cultivating a culture of adaptability, not only can the quality of care in temporary ICUs be improved, but also can the health care system be better prepared for future emergencies. These actions will help mitigate the risks associated with such conversions, ultimately benefiting patient safety, staff well-being and the overall effectiveness of health care services in crises.

Severity of topsoil compaction controls the impact of skid trails on soil ecological processes

Abstract Skid trails are a major management‐induced disturbance in temperate forest ecosystems with considerable impact on soil ecological processes that are so far poorly understood. In German forests, skid trails comprise 10%–20% of the forest area that is potentially affected by soil compaction through heavy machinery. We systematically investigated the influence of skid trails on physical, chemical and microbiological soil parameters at 84 paired plots across four Central European forest types. In low mountain forests with steeper topography, skid trails had more drastic effects than in lowland forests. Skid trails in low mountain areas showed a decrease in the C to N ratio of microbial biomass (MBC/MBN), as well as increased microbial (MBC/SOC) and enzyme activities leading to faster carbon turnover (lower C/N, EOC/EN) and increased CO2 losses (CO2/SOC) from the soil. The overall effects of the skid trails in lowland forests were small. On base‐poor soils, we found an increase in the MBC/MBN ratio, while skid trails in base‐rich lowland soils showed a reduction in CO2/SOC, suggesting a proportional increase in soil carbon storage. Regardless of region‐specific effects, the relative increase in the bulk density of the fine soil was identified as a ‘golden trait’ that determined the effects of skid trails on many soil parameters, as shown by negative correlations with SOC, N, MBC, MBN, MBP, MBC/SOC and CO2/SOC and positive ones with the activities of certain hydrolytic enzymes. Synthesis and applications: Our data clearly showed that carbon conversion processes and soil respiration leading to significant carbon and nutrient losses increased significantly on skid trails in low mountain regions with relatively steep slopes, which was in sharp contrast to lowland sites. The strong context dependence of our findings suggests that the mapping of soil conditions in terms of slope, substrate and moisture with high spatial resolution is mandatory to assess the vulnerability of sites to soil compaction by heavy machinery. Based on such vulnerability analysis, negative impacts can be minimised through the designation of permanently fixed skid trails, technical adaptation of vehicles (e.g. wide base tyres) as well as careful planning and timing of management operations that should be restricted to dry weather and soil moisture conditions or periods of frost.

A multicountry analysis of local government financial vulnerability during the 2020 pandemic considering systemic factors

AbstractThe COVID‐19 pandemic cut across geographical, sectorial, and policy boundaries and imposed difficult health, economic, and social challenges. Among many learnings, after the 2007–2008 global financial crisis and the austerity period that followed it, the economic and health crises forged by the COVID‐19 pandemic in 2020 offer an important experience to make local governments (LGs) more financially resilient and ready to deal with similar shocks.This paper builds on a recent framework to investigate the impact of the first wave of the COVID‐19 pandemic on LG financial vulnerability looking at both contingent and systemic aspects. It addresses the need for a multicountry perspective on the effects of the pandemic and responds to calls to test existing models. Seven countries were chosen to represent different administrative contexts and traditions to understand what factors impact the local level in a time of crisis. Results demonstrate that not only contingent aspects but also systemic factors and the initial level of financial vulnerability influenced the responses to the pandemic, confirming findings about the importance of initial conditions and “path dependency” by previous studies.

Water Supply Management Through an Innovative Dashboard Solution

The increased public awareness and stronger restrictions have led to a rising recognition of the significance of advanced technology, especially Geographic Information Systems (GIS), in the management of water resources. The use of GIS in water management is highlighted in this work, with particular attention paid to pollution control, hydrologic modelling, and analytical water supply systems. Furthermore, by combining six conditioning factors and applying vulnerability analysis and logistic regression, it offers a novel approach to leak detection in water distribution networks (WDNs). In order to support preventive maintenance and resource allocation, the model predicts vulnerable locations properly. It is also suggested to use machine learning algorithms to optimise turbine maintenance schedules as part of a predictive maintenance framework for hydroelectric power facilities. High accuracy rates are attained by the framework, which finds important variables for maintenance prediction. These methods provide useful instruments for effective management of water resources overall.

Integrated assessment of groundwater pollution vulnerability in Goulmima: a comparative analysis of DRASTIC and GOD methods

Integrated assessment of groundwater pollution vulnerability in Goulmima: a comparative analysis of DRASTIC and GOD methods

Evaluation of Climate Resilience Strategies in Vulnerable Communities in Ethiopia

Purpose: The aim of the study was to investigate on the evaluation of climate resilience strategies in vulnerable communities in Ethiopia. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: In Ethiopia, climate resilience strategies have been evaluated to address the increasing challenges faced by vulnerable communities. The Partners for Resilience program, implemented by CARE and other partners, has made significant strides in integrating disaster risk reduction, climate change adaptation, and ecosystem management and restoration, positively impacting over 1.2 million people. Efforts have focused on diversifying livelihoods, strengthening civil society's capacity for dialogue and advocacy, and rehabilitating water schemes and farmland. The Climate Vulnerability and Capacity Analysis (CVCA) by CARE Ethiopia has been instrumental in understanding local vulnerabilities and developing adaptive capacities against climate variability. Unique Contribution to Theory, Practice and Policy: Social-ecological systems theory (SES), community-based adaptation (CBA) theory &amp; vulnerability and resilience theory may be used to anchor future studies on evaluation of climate resilience strategies in vulnerable communities in Ethiopia. Strengthens community ownership, adaptive capacity, and sustainability of resilience interventions. Advocating for integrated policy frameworks that mainstream climate resilience into national and local development plans.

Reliability-Based Seismic Safety Assessment of the Metropolitan Cathedral of Brasília

Recent destructive earthquakes in Turkey (2023) with devastating effects have reawakened the discussion about seismic activity in Brazil and the vulnerability of the Brazilian buildings. Despite the lower magnitudes, national records should not be disregarded, as earthquakes with a magnitude below five may still cause loss of life and property damage. The assessment of existing RC buildings allows us to understand the performance of a structure during an earthquake and the adoption of mitigating measures. This paper preliminarily investigates the seismic vulnerability of the Metropolitan Cathedral in Brasilia, which was recognized as a World Heritage Site by ONU in 1987. The Rapid Visual Screening (RVS) procedure has been adopted for qualitative vulnerability assessment through the guidelines of the Japan Building Disaster Prevention Association at the procedure updated in accordance with the Brazilian reality. This research examined the structure under horizontal acceleration defined by national seismic code, and various scenarios are assumed as time aging, structural irregularities, and the level of importance of the structure. In this study, the Monte Carlo simulation is carried out to evaluate the level of safety. A performed analysis has shown that the examined building possesses the seismic capacity required against the expected earthquake motions. Even with reliability analysis, the structure achieves an acceptable level of safety. The results highlight the importance of a probabilistic approach to make reliable decisions on the conservation and rehabilitation of architectural heritage buildings.

Integrated assessment of groundwater vulnerability in arid areas combining classical vulnerability index and AHP model.

Groundwater is the main source of water for agriculture, industry, and families in arid areas. At present, there is an urgent need to protect groundwater due to human activities. In this study, the Qingshui River Basin was selected as the study area. Based on the DRASTIC model, the DRASTIC-Land use type (DRASTICL) model and the analytic hierarchy process-DRASTICL (AHP-DRASTICL) model were constructed by optimizing the indicators and weights. And the three models were applied to calculate the groundwater vulnerability index (GVI), and the groundwater vulnerability map (GVM) was drawn. The validation results of Spearman correlation coefficient show that the DRASTICL model and the AHP-DRASTICL model have higher correlation, which indicates that the optimized model is more accurate. Among them, the AHP-DRASTICL model has the highest correlation coefficient (ρ = 0.92), which is more in line with the actual situation. The results of this study can provide scientific guidance for the protection and utilization of groundwater in the Qingshui River Basin. And it is of guiding significance for the study of groundwater vulnerability, especially for groundwater management in arid and semi-arid areas.

Dynamic response and seismic vulnerability assessment of the near-fault steep slope

Existing field data demonstrates that structures situated near faults, such as slopes, dams, and bridges, are particularly vulnerable to damage. Near-fault ground motions exhibit marked disparities from their far-field counterparts, necessitating thorough investigation. This study conducts a comprehensive analysis of ground motion characteristics utilizing response spectra, Hilbert-Huang Transform (HHT), and marginal spectra to discern near-fault pulse-like ground motions (PLGMs), near-fault non-pulse-like ground motions (NPGMs), and far-fault ground motions (FFGMs). PLGMs distinguished by their heightened energy content, typically induce more pronounced amplification effects compared to NPGMs and FFGMs. Employing an efficacy criterion, optimal intensity measures (IMs) are identified and linked to dynamic response, referred to as engineering demand parameters (EDPs). Velocity-based IMs demonstrate substantial correlations across diverse ground motion types for both plastic volume ratio (PVR) and crest displacement (Dc). Lastly, probabilistic seismic demand models are leveraged to establish seismic vulnerability curves for steep slopes exposed to PLGMs and NPGMs. Notably, with Dc as the EDP, the exceedance probabilities associated with the three IMs under PLGMs generally surpass those under NPGMs. This underscores the propensity of PLGMs to trigger larger displacements in slopes, rendering them more prone to failure.

Threat Modeling for Cyber Warfare Against Less Cyber-Dependent Adversaries

Cyber warfare poses a substantial threat in today's interconnected world, where digital attacks can transcend physical boundaries and affect targets globally. Technologically, less advanced adversaries, such as smaller nations or organizations with limited resources, face unique challenges in defending against sophisticated cyber attacks from more advanced entities. This paper explores the threat landscape for these adversaries and proposes a tailored threat modeling framework to address their specific vulnerabilities and needs. By examining the evolution of cyber warfare, including historical incidents and the increasing sophistication of cyber attacks, the study highlights the limitations of existing threat modeling approaches like the Cyber Kill Chain, MITRE ATT&amp;CK Framework, and SWOT analysis when applied to less advanced adversaries. A comprehensive literature review underscores the gaps in current research, particularly the necessity for frameworks tailored to asymmetric technological capabilities. Employing a mixed methods approach, the research combines qualitative and quantitative data from primary sources, such as interviews with cybersecurity experts, and secondary sources, including existing literature and case studies. The proposed framework focuses on asset identification and classification, vulnerability assessment, threat analysis, and risk assessment. Proactive measures, such as basic cyber hygiene practices, advanced threat detection systems, and collaboration with technologically advanced allies, are recommended alongside reactive measures like incident response planning and disaster recovery. The importance of international cooperation and information sharing is also emphasized. Case studies of cyber incidents involving less advanced adversaries, such as the attacks on Estonia, Georgia, and Ukraine, validate the framework and demonstrate its practical application. The findings indicate that the tailored threat modeling framework effectively addresses the unique challenges faced by less advanced adversaries, enhancing their ability to mitigate risks and improve their cybersecurity posture. This study provides valuable insights and offers a practical framework to bolster defenses against cyber warfare, with future research needed to explore emerging threats and technologies further.