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Landslide Susceptibility Mapping using Statistical Information Value Model: A Case Study of part of Chamoli District, Uttarakhand India. 基于统计信息值模型的滑坡易感性制图——以印度北阿坎德邦Chamoli地区部分地区为例
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-11-05 DOI: 10.1111/risa.70141
Anand Kumar, Shruti Kanga, Upasana Choudhury, Suraj Kumar Singh, Rakesh Singh Rana, Gowhar Meraj, Pankaj Kumar

Landslides have become increasingly frequent and destructive in Uttarakhand, leading to substantial loss of life and significant damage to infrastructure. This research focuses on generating a detailed landslide susceptibility map for a selected area in Chamoli district, Uttarakhand, by integrating remote sensing and geographical information system (GIS) techniques. Twelve critical factors influencing landslide occurrence, such as slope, aspect, vegetation cover, proximity to geological structures, distance from roads, elevation, curvature, topographic wetness index (TWI), stream power index (SPI), drainage proximity, and lithology, were considered. The Statistical Information Value Model (SIVM) was used to assess the contribution (weight) of each factor class toward landslide occurrence. These derived weights were then integrated using a weighted overlay method to produce the final landslide susceptibility map. The predictive accuracy of the model was validated through receiver operating characteristic (ROC) analysis, achieving an area under the curve (AUC) value of 0.72. The results demonstrate that the SIVM-based weighted overlay approach provides a reliable tool for identifying landslide-prone zones, offering valuable insights for land use planning and disaster mitigation.

在北阿坎德邦,山体滑坡变得越来越频繁,破坏性也越来越大,导致大量人员丧生,基础设施遭到严重破坏。本研究的重点是通过整合遥感和地理信息系统(GIS)技术,为北阿坎德邦Chamoli地区的选定地区生成详细的滑坡易感性地图。考虑了影响滑坡发生的12个关键因素,如坡度、坡向、植被覆盖、与地质构造的接近程度、与道路的距离、高程、曲率、地形湿度指数(TWI)、水流功率指数(SPI)、排水接近程度和岩性。采用统计信息价值模型(SIVM)对各因素类别对滑坡发生的贡献(权重)进行了评价。然后使用加权叠加法对这些导出的权重进行综合,生成最终的滑坡易感性图。通过受试者工作特征(ROC)分析验证了模型的预测准确性,曲线下面积(AUC)值为0.72。结果表明,基于sivm的加权叠加方法为确定滑坡易发区提供了可靠的工具,为土地利用规划和减灾提供了有价值的见解。
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引用次数: 0
Crisis and Risk Governance of Cross-Regional Embodied Carbon Transfers: A Game Theory and Multi-Agent Network Analysis. 跨区域隐含碳转移的危机与风险治理:博弈论与多主体网络分析。
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-11-26 DOI: 10.1111/risa.70154
Zeyu Xing, Lupeng Zhang, Debin Fang, Fujun Jiang

As global carbon neutrality ambitions intensify, cross-regional embodied carbon transfers via inter-city trade increasingly pose complex governance risks and crises. Employing an environmentally extended multi-regional input-output (EE-MRIO) framework integrated with evolutionary game theory and multi-agent network analysis, this study critically investigates strategic governance responses to these risks within hierarchical administrative contexts. We introduce a refined carbon accounting approach that explicitly merges production-based and consumption-based emissions, significantly enhancing the precision and fairness of accountability mechanisms. Using multiyear data on 313 Chinese cities, we identify critical thresholds in carbon pricing that decisively shape cooperative and non-cooperative behavior in carbon mitigation. Furthermore, network structure profoundly affects governance outcomes-small-world topologies rapidly diffuse cooperative norms, whereas scale-free networks exacerbate vulnerabilities to strategic defection and systemic risk. This research offers robust theoretical advancements by clarifying the roles of strategic interactions, network topologies, and administrative incentives in shaping embodied carbon governance. Practically, we provide actionable policy interventions for mitigating systemic inefficiencies and resolving equity challenges linked to carbon leakage, trade-induced risks, and regional crises. By combining theoretical rigor with policy-oriented insights, our integrated methodological approach sets a precedent for effective and equitable climate risk governance, broadly adaptable beyond China's specific context.

随着全球碳中和目标的增强,通过城市间贸易进行的跨区域隐含碳转移日益构成复杂的治理风险和危机。本研究采用环境扩展的多区域投入产出(EE-MRIO)框架,结合进化博弈论和多智能体网络分析,批判性地探讨了在分层管理背景下对这些风险的战略治理响应。我们引入了一种精细化的碳核算方法,明确合并了基于生产和消费的排放,显著提高了问责机制的准确性和公平性。利用中国313个城市的多年数据,我们确定了碳定价的关键阈值,这些阈值决定性地塑造了碳减排中的合作与非合作行为。此外,网络结构深刻地影响着治理结果——小世界拓扑结构迅速扩散合作规范,而无标度网络则加剧了战略背叛和系统风险的脆弱性。本研究通过阐明战略互动、网络拓扑结构和行政激励在塑造具体碳治理中的作用,提供了强有力的理论进展。实际上,我们提供了可操作的政策干预措施,以减轻系统性效率低下,并解决与碳泄漏、贸易风险和区域危机相关的公平挑战。通过将理论的严谨性与政策导向的洞察力相结合,我们的综合方法为有效和公平的气候风险治理开创了先例,具有广泛的适应性,超出了中国的具体情况。
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引用次数: 0
Risk-aware autonomous search and rescue with multiagent reinforcement learning. 基于多智能体强化学习的风险感知自主搜索与救援。
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-07-05 DOI: 10.1111/risa.70067
Aowabin Rahman, Salman Shuvo, Samrat Chatterjee, Mahantesh Halappanavar, Terje Aven

Autonomous navigation in dynamic high-consequence environments, such as search and rescue (SAR) missions, often relies on multiagent robotic systems that need to learn and adapt to changing conditions. Adversarial risks can introduce further challenges in such a setting where an autonomous agent may exhibit deviations in their learned actions from training to testing. Moreover, the uncertain environment itself may also evolve with additional obstacles that can emerge during testing compared to conditions when algorithmic training of autonomous agents was performed. In this paper, we first focus on mathematically formulating the autonomous SAR problem via a risk-aware multiagent reinforcement learning approach. Thereafter, we design and implement numerical experiments to evaluate our approach under diverse hazard scenarios with a centralized training and decentralized testing paradigm. Finally, we discuss our results and steps for further research.

动态高后果环境中的自主导航,如搜索和救援(SAR)任务,通常依赖于需要学习和适应不断变化的条件的多智能体机器人系统。在这种情况下,自主代理可能会在从训练到测试的学习行为中表现出偏差,对抗性风险会带来进一步的挑战。此外,与自主代理进行算法训练时的情况相比,在测试过程中,不确定的环境本身也可能会出现额外的障碍。在本文中,我们首先关注通过风险感知多智能体强化学习方法在数学上制定自主SAR问题。随后,我们设计并实施了数值实验,通过集中训练和分散测试范式来评估我们的方法在不同危险情景下的效果。最后,我们讨论了我们的结果和进一步研究的步骤。
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引用次数: 0
Assessing global pandemic risks from emerging infectious diseases and high containment laboratory leaks: A country-level spatial network SIR model analysis. 评估来自新发传染病和高度封闭实验室泄漏的全球大流行风险:国家级空间网络SIR模型分析。
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-10-30 DOI: 10.1111/risa.70070
Ross J Tieman, Pedro Adami Oliboni, Simeon Campos

Future pandemics could arise from several sources, notably, emerging infectious diseases (EID); and lab leaks from high containment biological laboratories (HCBL). Recent advances in infectious disease, information technology, and biotechnology provide building blocks to reduce pandemic risk if deployed intelligently. However, the global nature of infectious diseases, distribution of HCBLs, and increasing complexity of transmission dynamics due to travel networks make it difficult to determine how to best deploy mitigation efforts. Increasing understanding of the risk landscape posed by EID and HCBL lab leaks could improve risk reduction efforts. The presented paper develops a country-level spatial network susceptible-infected-removed model based on global travel network data and relative risk measures of potential origin sources, EID, and lab leaks from biological safety level 3+ and 4 labs, to explore expected infections over the first 30 days of a pandemic. Model outputs indicate that EID and lab leaks in India, the USA, and China are most impacted at day 30. For EID, expected infections shift from high EID origin potential countries at day 10 to the USA, India, and China, while for lab leaks, the USA and India start with high lab leak potential. With respect to model uncertainties and limitations, results indicate several large, wealthy countries are influential to pandemic risk from both EID and lab leaks, indicating high leverage points for mitigation efforts.

未来的大流行病可能有几个来源,特别是新发传染病;以及高安全度生物实验室(HCBL)的实验室泄漏。传染病、信息技术和生物技术方面的最新进展为明智地部署减少大流行风险提供了基础。然而,由于传染病的全球性、高氯氟烃的分布以及由于旅行网络导致的传播动态日益复杂,很难确定如何最好地部署缓解工作。加深对EID和HCBL实验室泄漏所带来的风险格局的了解,可以改善降低风险的努力。本文基于全球旅行网络数据和潜在来源、EID和生物安全级别3+和4级实验室泄漏的相对风险度量,开发了一个国家级空间网络易感感染-移除模型,以探索大流行前30天的预期感染情况。模型输出表明,印度、美国和中国的EID和实验室泄漏在第30天受到的影响最大。对于EID,预期感染在第10天从高EID起源潜力国家转移到美国、印度和中国,而对于实验室泄漏,美国和印度从高实验室泄漏潜力开始。关于模型的不确定性和局限性,结果表明,几个富裕的大国对EID和实验室泄漏造成的大流行风险都有影响,这表明了缓解努力的高杠杆点。
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引用次数: 0
Game-Theoretic Optimization on School Safety: Resource Allocation Against Strategic Attacks. 学校安全的博弈论优化:针对战略攻击的资源配置。
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-12-05 DOI: 10.1111/risa.70156
Sabiha Unal Eyi, Jun Zhuang

School security remains a critical concern due to the increasing frequency of violent incidents, requiring a strategic balance between physical security measures and mental health programs. This study develops a game-theoretic framework to model the interaction between a school as the defender and a potential attacker, aiming to identify optimal investment decisions across two complementary layers of defense. Numerical illustrations calibrated with data from U.S. school shootings provide empirical support for the analysis. Through one-way and two-way sensitivity analyses, robustness tests, and scenario-based indifference curve analysis, we explore how attacker and defender valuations, intervention effectiveness, and defensive costs influence equilibrium strategies. The findings show that physical security measures have the strongest deterrent effect, but lasting protection depends on balanced investment in both security and mental health once their effectiveness exceeds critical thresholds. While physical security offers immediate deterrence, mental health interventions are essential for addressing underlying risk factors, emphasizing the complementary nature of the two approaches. The framework contributes to evidence-based decision-making for educational institutions and suggests future extensions to include external threats, incomplete information, and dynamic investment strategies.

由于暴力事件日益频繁,学校安全仍然是一个关键问题,需要在人身安全措施和心理健康计划之间取得战略平衡。本研究开发了一个博弈论框架来模拟作为防御者和潜在攻击者的学校之间的相互作用,旨在确定跨两个互补防御层的最佳投资决策。用美国校园枪击案数据校准的数值插图为分析提供了经验支持。通过单向和双向敏感性分析、鲁棒性检验和基于场景的无差异曲线分析,我们探讨了攻击者和防御者的估值、干预有效性和防御成本如何影响均衡策略。研究结果表明,物理安全措施具有最强的威慑作用,但一旦其有效性超过临界阈值,持久的保护取决于在安全和心理健康方面的平衡投资。虽然人身安全可以立即起到威慑作用,但心理健康干预措施对于解决潜在的风险因素至关重要,强调了这两种方法的互补性。该框架有助于教育机构的循证决策,并建议未来扩展到包括外部威胁、不完全信息和动态投资策略。
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引用次数: 0
Integrated testing strategies for cost-sensitive time-efficient hazard classification of new chemicals: The case of skin sensitization. 新化学品成本敏感、时效性危害分类的综合测试策略:皮肤致敏的案例。
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-02-17 DOI: 10.1111/risa.17717
Marko Raseta, Jon Pitchford, James Cussens, John Doe

We offer an alternative approach to toxicological risk assessment of new chemicals. We combine Operations Research techniques with those from Machine Learning to tackle the decision-making process. More specifically, we use Markov decision processes and Bayesian networks to derive the optimal cost-sensitive time-efficient Integrated Testing Strategies for chemical hazard classification under minimal expected cost in a mathematically rigorous fashion. We develop Bayesian networks which outperform state-of-the-art mechanistic causal models previously reported. More specifically, these models exhibit accuracy of 90% and sensitivity and specificity of 93% and 84%, respectively. Moreover, the inferred Bayesian networks are of considerably simpler structure as they comprise only the permeation coefficient, octanol/water coefficient, and TIMES software compared to their counterparts already in print, which comprise 15 descriptors. We use these simplified causal models to study the effect of varying misclassification costs on the nature of the optimal policy by means of sensitivity analysis. We note such analysis was previously computationally infeasible due to the fact that the variables which comprised the mechanistic model were categorical assuming a large number of possible values. We find that a variety of optimal policies can emerge subject to different misclassification costs assumed. Theoretical modeling framework developed is illustrated on the concrete example of hazard classification of skin allergens of previously unknown toxicological characteristics via integrating data obtained from in silico assays alone thus contributing to the literature of toxicological decision making based on nonanimal tests.

我们为新化学品的毒理学风险评估提供了另一种方法。我们将运筹学技术与机器学习技术相结合来解决决策过程。更具体地说,我们使用马尔可夫决策过程和贝叶斯网络,以数学上严格的方式,在最小的期望成本下,推导出最优的成本敏感、时间有效的化学危害分类综合测试策略。我们开发的贝叶斯网络优于先前报道的最先进的机械因果模型。更具体地说,这些模型的准确率为90%,灵敏度和特异性分别为93%和84%。此外,与已出版的同类产品(包含15个描述符)相比,推断出的贝叶斯网络结构简单得多,因为它们仅包含渗透系数、辛醇/水系数和TIMES软件。我们利用这些简化的因果模型,通过敏感性分析研究了不同错误分类成本对最优政策性质的影响。我们注意到,由于组成机制模型的变量是分类假设大量可能值的事实,这种分析以前在计算上是不可行的。我们发现,假设不同的错误分类代价会产生各种最优策略。通过整合仅从计算机分析中获得的数据,对先前未知毒理学特征的皮肤过敏原进行危害分类的具体示例说明了所开发的理论建模框架,从而有助于基于非动物试验的毒理学决策的文献。
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引用次数: 0
Will emergency order shifting perform better than recovery waiting at costs of carbon tax and carbon emission reduction? 以碳税和碳减排为代价,紧急订单转移是否比恢复等待更好?
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-06-06 DOI: 10.1111/risa.70051
Baozhuang Niu, Lihua Zhu, Jian Dong, Jinbo Song

In recent years, frequent extreme disasters have challenged supply chain operations while smart risk warning systems are developed to facilitate firms' emergency order shifting to a new manufacturer. It is noted that reliable manufacturers are usually located in countries/regions levying carbon tax to achieve high ESG scores, so we consider a cross-border supply chain consisting of a global brand, a local brand, an overseas manufacturer and a local manufacturer to investigate the main tradeoffs for the global brand to emergently shift orders from the overseas manufacturer facing disruptions to a stable local manufacturer subject to carbon tax cost. The global brand has the option to wait for the recovery of overseas production but if it chooses emergent order shifting, it has to invest in carbon emission reduction due to ESG requirements. We intriguingly find that even though emergency order shifting helps avert delays caused by production disruptions, a more resilient supply chain does not necessarily lead to a higher profit for the global brand, depending on factors such as the relative market size, carbon tax cost, and the efficiency of carbon reduction investment. We also find that the global brand's emergency order shifting enables Pareto improvement of economic and environmental sustainability, but the win-win opportunities for both the global and local brand only appear under the recovery waiting strategy. So it is generally hard to coordinate the stakeholders' incentives to jointly optimize the ESG scores.

近年来,极端灾害频发给供应链运作带来了挑战,智能风险预警系统的开发促进了企业的紧急订单转移到新的制造商。值得注意的是,可靠的制造商通常位于征收碳税以获得高ESG分数的国家/地区,因此我们考虑一个由全球品牌、当地品牌、海外制造商和当地制造商组成的跨境供应链,以调查全球品牌在面临碳税成本的情况下紧急将订单从海外制造商转移到稳定的当地制造商时的主要权衡。全球品牌可以选择等待海外生产的恢复,但如果选择紧急订单转移,则必须根据ESG要求进行碳减排投资。我们有趣地发现,尽管紧急订单转移有助于避免生产中断造成的延迟,但更具弹性的供应链并不一定会给全球品牌带来更高的利润,这取决于相对市场规模、碳税成本和碳减排投资效率等因素。我们还发现,全球品牌的紧急订单转移能够实现经济和环境可持续性的帕累托改善,但全球品牌和本土品牌的双赢机会只有在复苏等待策略下才会出现。因此,协调利益相关方共同优化ESG评分的动机通常比较困难。
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引用次数: 0
Risks of ignoring uncertainty propagation in AI-augmented security pipelines. 忽视人工智能增强安全管道中不确定性传播的风险。
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-06-22 DOI: 10.1111/risa.70059
Emanuele Mezzi, Aurora Papotti, Fabio Massacci, Katja Tuma

The use of AI technologies is being integrated into the secure development of software-based systems, with an increasing trend of composing AI-based subsystems (with uncertain levels of performance) into automated pipelines. This presents a fundamental research challenge and seriously threatens safety-critical domains. Despite the existing knowledge about uncertainty in risk analysis, no previous work has estimated the uncertainty of AI-augmented systems given the propagation of errors in the pipeline. We provide the formal underpinnings for capturing uncertainty propagation, develop a simulator to quantify uncertainty, and evaluate the simulation of propagating errors with one case study. We discuss the generalizability of our approach and its limitations and present recommendations for evaluation policies concerning AI systems. Future work includes extending the approach by relaxing the remaining assumptions and by experimenting with a real system.

人工智能技术的使用正被集成到基于软件的系统的安全开发中,将基于人工智能的子系统(具有不确定的性能水平)组合到自动化管道中的趋势日益增加。这对基础研究提出了挑战,并严重威胁到安全关键领域。尽管已有关于风险分析中的不确定性的知识,但没有先前的工作估计人工智能增强系统在管道中传播错误的不确定性。我们提供了捕获不确定性传播的形式化基础,开发了一个模拟器来量化不确定性,并通过一个案例研究评估传播误差的模拟。我们讨论了我们的方法的概括性及其局限性,并提出了有关人工智能系统评估政策的建议。未来的工作包括通过放松剩余的假设和用实际系统进行实验来扩展该方法。
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引用次数: 0
Model averaging with logistic autoregressive conditional peak over threshold models for regional smog. 区域雾霾的logistic自回归条件峰值超过阈值模型平均。
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-07-07 DOI: 10.1111/risa.70069
Chunli Huang, Xu Zhao, Fengying Zhang, Haiqing Chen, Ruoqi Song, Guangwen Ma, Weihu Cheng

We propose a novel dynamic generalized Pareto distribution (GPD) framework for modeling the time-dependent behavior of the peak over threshold (POT) in extreme smog (PM2.5) time series. First, unlike static GPD, three dynamic autoregressive conditional generalized Pareto (ACP) models are introduced. Specifically, in these three dynamic models, the exceedances of air pollutant concentration are modeled by a GPD with time-dependent scale and shape parameters conditioned on past PM2.5 and other air quality factors (SO2, NO2, CO) and weather factors (daily average temperature, average relative humidity, average wind speed). Second, unlike the recent studies of ACP models, we impose a logistic function autoregressive structure on the scale and shape parameters of the ACP models, which has simple calculation and flexible modeling for the scale and shape parameters, since the logistic function is used to mean that the changes in the long memory parameter occur in a continuous manner and often applied in time series models. Third, the model averaging method is applied to improve predictive performance using AIC and BIC criteria to select combined weights of the three ACP models. In addition, based on goodness-of-fit tests, the thresholds of the three ACP models are chosen by eight automatic threshold selection procedures to avoid subjectively assigning a certain value as the threshold. Maximum likelihood estimation (MLE) is employed to estimate parameters of the ACP models and its statistical properties are investigated. Various simulation studies and an example of real data in PM2.5 time series demonstrate the superiority of the proposed ACP models and the stability of the MLE.

我们提出了一种新的动态广义帕累托分布(GPD)框架,用于模拟极端雾霾(PM2.5)时间序列中峰值超过阈值(POT)的时间依赖性行为。首先,与静态广义帕累托模型不同,本文引入了三种动态自回归条件广义帕累托模型。具体而言,在这三个动态模型中,空气污染物浓度的超标是通过GPD模型来模拟的,GPD具有随时间变化的尺度和形状参数,这些参数取决于过去PM2.5和其他空气质量因子(SO2、NO2、CO)以及天气因子(日平均温度、平均相对湿度、平均风速)。其次,与目前ACP模型的研究不同,我们在ACP模型的尺度和形状参数上施加了逻辑函数自回归结构,该结构计算简单,对尺度和形状参数建模灵活,因为逻辑函数用于表示长记忆参数的变化以连续的方式发生,通常用于时间序列模型。第三,采用模型平均法,利用AIC和BIC准则选择三个ACP模型的组合权重,提高预测性能。此外,在拟合优度检验的基础上,通过8个自动阈值选择程序来选择三个ACP模型的阈值,避免主观地指定某个值作为阈值。采用极大似然估计(MLE)对ACP模型的参数进行估计,并研究了其统计性质。各种模拟研究和PM2.5时间序列的实际数据实例证明了所提出的ACP模型的优越性和MLE的稳定性。
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引用次数: 0
Cyber Resilience and Strategic Stability: Securing Nuclear Facilities in the Digital Age. 网络弹性和战略稳定性:数字时代核设施的安全。
IF 3.3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-12-01 Epub Date: 2025-10-28 DOI: 10.1111/risa.70136
Syed Muhammad Saad Zaidi, Muhammad Ehsan, Sardar Jehanzaib Ghalib

In an era of increasing digitization, nuclear command systems and power plants are becoming vulnerable to cyberattacks that can disrupt operations and undermine deterrence. This article examines the evolving threat landscape, drawing on literature and documented incidents of cyber intrusions into nuclear systems to identify critical technical and policy vulnerabilities. It argues that such intrusions risk eroding second-strike credibility and may create incentives for preemptive action, thereby destabilizing strategic balances. Although regulatory bodies and international organizations have issued cybersecurity guidelines for nuclear facilities, implementation remains inconsistent. To address these challenges, the study proposes a set of resilience measures encompassing advanced technical safeguards, specialized workforce training, the establishment of international norms, and enhanced crisis communication protocols. Strengthening the cyber resilience of both civilian and military nuclear assets is presented as an urgent imperative for maintaining global security and strategic stability in the digital age.

在日益数字化的时代,核指挥系统和发电厂正变得容易受到网络攻击,这些攻击可能会破坏行动并削弱威慑。本文研究了不断变化的威胁形势,借鉴文献和记录在案的核系统网络入侵事件,以确定关键的技术和政策漏洞。它认为,这种入侵有可能侵蚀二次打击的可信度,并可能促使采取先发制人的行动,从而破坏战略平衡。尽管监管机构和国际组织已经发布了核设施网络安全指导方针,但实施情况仍不一致。为了应对这些挑战,该研究提出了一套弹性措施,包括先进的技术保障措施、专门的劳动力培训、建立国际规范和加强危机沟通协议。加强民用和军用核资产的网络弹性被认为是维护数字时代全球安全和战略稳定的迫切需要。
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引用次数: 0
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