International Journal of Critical Infrastructure Protection最新文献

{"title":"Quantification of seismic resilience of water distribution networks considering interdependency using Dempster-Shafer theory","authors":"Z. Zarebidaki,&nbsp;B. Omidvar","doi":"10.1016/j.ijcip.2025.100809","DOIUrl":"10.1016/j.ijcip.2025.100809","url":null,"abstract":"<div><div>Providing potable water, one of the most vital human needs has always been a major challenge in natural disaster management. This study focuses on the challenge of ensuring the resilience of urban water infrastructure in the face of disasters. The main goal is to present the resilience indices of the water infrastructure in a metropolitan area after an earthquake, considering its dependence on electricity, transportation, and telecommunication infrastructures using the Dempster-Shafer theory of evidence.</div><div>The results show that the water infrastructure will be more resilient in the moderate earthquake scenario than the strong one. The resilience enhancement of transportation and telecommunication items has the most positive effect on the water system resilience, increasing by &gt;48 percent for the strong earthquake scenario. The increase in water infrastructure resilience would be up to 24 percent by raising the resilience belief values of each technical, non-technical, and telecommunication component for the moderate earthquake scenario. The results reveal notable insights into the vulnerability of interdependent infrastructures under earthquake scenarios, having important implications for the risk analysis and resilience management of various infrastructures.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"51 ","pages":"Article 100809"},"PeriodicalIF":5.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145362599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust trust management in Intelligent Transportation System: A machine learning approach","authors":"Ahmed Danladi Abdullahi ,&nbsp;Erfan Bahrami ,&nbsp;Tooska Dargahi ,&nbsp;Mohammed Al-Khalidi ,&nbsp;Mohammad Hammoudeh","doi":"10.1016/j.ijcip.2025.100812","DOIUrl":"10.1016/j.ijcip.2025.100812","url":null,"abstract":"<div><div>Intelligent Transportation Systems (ITS) are revolutionising modern mobility by leveraging advancements in 5G technology, smart sensors, and sophisticated data analytics. These advancements facilitate the exchange and decision making of information in real time, improving safety and efficiency. However, the heterogeneous and loosely connected nature of the ITS components presents significant challenges in evaluating and managing trust within the ecosystem. Traditional approaches, such as blockchain-based consensus mechanisms, peer-to-peer voting systems, and static rule-based trust models, struggle to evaluate trust uniformly across diverse components and data types in real time, leaving the system vulnerable to various threats. Recent studies explored Machine Learning (ML) techniques to address trust management in ITS. These advanced approaches offer promising solutions for processing large volumes of heterogeneous data, identifying complex patterns, and adapting to dynamic environments. However, most existing ML-based solutions focus on assessing trust for particular components, such as vehicles and roadside units (RSUs), rather than addressing the collective trust of the entire ITS ecosystem.</div><div>This paper proposes a novel ML-based dynamic trust management system termed MLT. It employs a feedforward neural network and the Levenberg–Marquardt Algorithm to dynamically assess the trustworthiness of ITS components. The system incorporates a dynamic time decay factor and continuously updates the trust scores, allowing effective identification and isolation of malicious actors. Through extensive simulations, MLT outperforms baseline models by up to 10% in precision and 9% in F-measure across various attack scenarios. These results highlight the superior performance of MLT in accuracy and robustness compared to existing trust management models.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"51 ","pages":"Article 100812"},"PeriodicalIF":5.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145623564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Securing cyber-physical systems: Attack detection and isolation in power grid AGC","authors":"Muhammad Asim Abbasi ,&nbsp;Aadil Sarwar Khan ,&nbsp;Shiping Huang ,&nbsp;Mansoor Zahoor Qadri ,&nbsp;Li Guo","doi":"10.1016/j.ijcip.2025.100806","DOIUrl":"10.1016/j.ijcip.2025.100806","url":null,"abstract":"<div><div>Modern power systems integrate cutting-edge communication and computational technologies with the physical infrastructure, making them a good example of a cyber–physical system (CPS). Like any other CPS, the power system is prone to cyber attacks, particularly in automatic generation control (AGC). AGC in the power system relies on the communication network and is therefore vulnerable to attacks. This paper studies the detection and isolation of multiple simultaneous attacks against multi-area AGC in the presence of renewable energy resources (RERs) and electric vehicles (EVs). The impact of EVs and RERs is modeled as unknown inputs/disturbances. A directional unknown input observer (DUIO) based approach is proposed to assure simultaneous disturbance decoupling and attack isolation with lesser computational burden than the existing schemes. The effectiveness of the proposed method is validated through comprehensive case studies and simulations on a two-area interconnected AGC power system, representing a typical multi-region power grid with renewable energy and electric vehicle integration.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"51 ","pages":"Article 100806"},"PeriodicalIF":5.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145319496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel data–intelligence–driven three–stage dynamic model for resilience assessment in an emergency material support system","authors":"Weilan Suo ,&nbsp;Wenjie Xu ,&nbsp;Longfei Li ,&nbsp;Xiaolei Sun","doi":"10.1016/j.ijcip.2025.100804","DOIUrl":"10.1016/j.ijcip.2025.100804","url":null,"abstract":"<div><div>Resilience is a crucial benchmark in characterizing the comprehensive capability of the emergency material support system (EMSS) to respond to major risk events. Given the involvement of multiple stakeholders, multiple stages and dynamic evolution, EMSS resilience assessment remains a challenge. Therefore, we attempt to develop a novel data–intelligence–driven three–stage dynamic model based on multi–source text data and multi–expert knowledge. In Stage 1, a large language models–enhanced named entity recognition model is proposed to extract and analyze EMSS risk events, providing a foundational dataset for scenario construction. In Stage 2, an ontology–based scenario construction model is proposed to abstract risk events into ontological concepts, providing a feature reference for the hierarchical system of assessment criteria. In Stage 3, a feature–matching assessment model is proposed to quantify the profile of EMSS resilience, where the uncertainty and variability in experts’ perceptions of resilience feature are addressed. Subsequently, the model effectiveness is demonstrated in a case study, in which the key criteria and improvement paths for EMSS resilience are identified. This study provides a holistic solution and efficient methodology for EMSS resilience assessment, offering significant insights into a multifaceted recognition of EMSS resilience to risk scenarios.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"51 ","pages":"Article 100804"},"PeriodicalIF":5.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying cyber attack vulnerabilities in the main lubricating oil system of marine propulsion units","authors":"Yigit Gülmez ,&nbsp;Olgun Konur ,&nbsp;Muhammed Erbas ,&nbsp;Sanja Bauk","doi":"10.1016/j.ijcip.2025.100810","DOIUrl":"10.1016/j.ijcip.2025.100810","url":null,"abstract":"<div><div>This study investigates the cyber vulnerabilities of the main engine lubricating oil system in marine vessels through a detailed simulation model. It focuses on the impact of cyber-attacks targeting temperature control equipment and sensors, using a MATLAB Simulink model to simulate various attack scenarios and assess their effects on system behavior. The research identifies critical components prone to cyber threats and quantifies their risk levels using a novel integration of Monte Carlo simulations, safety margins methodologies and a full mission engine room simulator. The results highlight the impact of each specific cyber-attack on the temperature of the lubricating oil in a marine vessel's main engine, showing how substantially each type of cyber-attack can increase temperatures and potentially lead to catastrophic engine failures. Based on these insights, the study proposes applicable strategies to enhance the cyber resilience of marine vessel systems, highlighting the need for advanced detection mechanisms and comprehensive cyber defense measures. This study not only explores specific vulnerabilities but also provides further research on maritime cybersecurity.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"51 ","pages":"Article 100810"},"PeriodicalIF":5.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145362600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protection of critical infrastructures in times of peace and war","authors":"Roberto Setola","doi":"10.1016/S1874-5482(25)00060-5","DOIUrl":"10.1016/S1874-5482(25)00060-5","url":null,"abstract":"","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"50 ","pages":"Article 100799"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Securing the nuclear supply chain: Addressing the issue of counterfeiting","authors":"Christopher Hobbs ,&nbsp;Zoha Naser ,&nbsp;Sarah Tzinieris","doi":"10.1016/j.ijcip.2025.100767","DOIUrl":"10.1016/j.ijcip.2025.100767","url":null,"abstract":"<div><div>In 2024, exploding pagers and walkie-talkies in Lebanon dramatically highlighted the importance of supply chain security and the risk that counterfeiting can pose. This article seeks to explore these issues in the nuclear context. Drawing on new empirical research, it examines how counterfeited materials, items, and technologies have found their way into nuclear supply chains and ultimately to facilities, exploring the impact of this and how the international community has responded. It finds that although counterfeits can and indeed have created significant nuclear risks, historically this issue has received relatively little attention. Here, a general lack of awareness, an overly narrow focus on their impact on critical safety systems, and the absence of comprehensive reporting mechanisms mean that the number of known counterfeits that have penetrated nuclear facilities globally is likely to be significantly underestimated. Although new international efforts in this area aimed at securing the nuclear supply chain have been launched in recent years, there remains much to be done, with considerable variation in the maturity of different countries and organizations’ approaches to this issue.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"50 ","pages":"Article 100767"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cyber-resilient mechanism for detection, classification and mitigation of intrusion on synchrophasor data in power networks","authors":"Soma Bhattacharya,&nbsp;Brundavanam Seshasai,&nbsp;Ebha Koley,&nbsp;Subhojit Ghosh","doi":"10.1016/j.ijcip.2025.100785","DOIUrl":"10.1016/j.ijcip.2025.100785","url":null,"abstract":"<div><div>In recent times, owing to their ability in providing accurate synchronized phasor information with global positioning system (GPS) based common time reference, phasor measurement units (PMUs) have emerged as one of the most significant components of the wide-area monitoring system of modern power networks. However, the use of public GPS signal and increased dependence on the communication infrastructure for transmitting phasor information have made the PMU (also referred to as synchrophasor) dependent operations highly vulnerable to the cyber intrusions. Intrusions on synchrophasor data is generally executed by either manipulating the common time reference (referred to as time synchronization attack (TSA)) or by injecting a falsified data into the actual PMU acquired signal to recreate a non-existing scenario (referred to as replay attack (RA)). For both the attacks, the acquisition of manipulated data at the control centre negatively disturbs the wide-area monitoring and control operations, which might even lead the network to blackout. Motivated by the requirement of increasing the resiliency of power networks against TSA and RA, the development of an accurate, reliable and comprehensive scheme for detecting, classifying and mitigating the impact of phasor intrusions has been sought in the present work. The three-stage mechanism involves processing of the phasor data acquired from multiple PMUs using bi-directional gated recurrent unit (Bi-GRU) based classifiers to detect intrusion (first stage) and further classify the type of intrusion as TSA or RA (second stage). Post-intrusion classification, in the final stage, Bessel interpolation is applied to filter out the spoofed data and further replace it with intrusion-free (pre-attack) data. The proposed scheme has been extensively validated for practical settings in real-time testbed with regards to detecting intrusions, distinguishing intrusions from contingencies, classifying intrusion and estimating the state variables closer to the pre-attack levels.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"50 ","pages":"Article 100785"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CyberSentry: Enhancing SCADA security through advanced deep learning and optimization strategies","authors":"Alaa O. Khadidos ,&nbsp;Adil O. Khadidos ,&nbsp;Shitharth Selvarajan ,&nbsp;Taher Al-Shehari ,&nbsp;Nasser A Alsadhan ,&nbsp;Subhav Singh","doi":"10.1016/j.ijcip.2025.100782","DOIUrl":"10.1016/j.ijcip.2025.100782","url":null,"abstract":"<div><div>SCADA systems form the core of infrastructural facilities, including power grids, water treatment facilities, and industrial processes. Changing cyber threats present increasingly sophisticated attacks against which traditional security models inadequately protect SCADA systems. These traditional models usually have drawbacks in the way of inadequate feature selection, inefficiency in detecting most attacks, and suboptimal parameter tuning, which cause vulnerabilities and reduce resilience in systems. This paper presents CyberSentry, a new security framework designed to overcome limitations so as to provide robust protection for SCADA systems. These three modules makeup CyberSentry: the RMIG feature selection model, tri-fusion net for attack detection, and Parrot-Levy Blend Optimization (PLBO) for parameter tuning. The Recursive Multi-Correlation-based Information Gain (RMIG) feature selection model enhances accuracy in detection by optimizing the set of fatal features through recursive multi-correlation analysis by Information Gain prioritization. The Tri-Fusion Net combines anomaly detection, signature-based detection, and machine learning classifiers to enhance the detection versatility and robustness. The PLBO module ensures efficient and dynamic tuning for the parameters through undocumented Parrot and Levy optimization techniques. The proposed CyberSentry framework integrates, within a unified architecture, anomaly detection, signature-based detection, and machine learning classifiers to enhance the security of SCADA systems against diverse cyber threats. Features extracted in this manner are analyzed using machine learning classifiers that exploit their predictive capabilities for robust threat classification. The proposed approaches are fused within the Tri-Fusion Net to complement each other in areas where the separate methods lack certain strengths. This, therefore, ensures broad threat detection, as is validated by extensive testing with various datasets for the assurance of superiority in accuracy and reliability. Validated and tested against a wide variety of datasets, CyberSentry demonstrates an overall accuracy of 99.5 % and a loss of 0.32, proving that this method is both effective and reliable.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"50 ","pages":"Article 100782"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing cybersecurity in railways: Machine learning approaches for attack detection","authors":"Beatriz Otero Calviño,&nbsp;Eva Rodriguez,&nbsp;Juan José Costa,&nbsp;Mercedes Oriol","doi":"10.1016/j.ijcip.2025.100788","DOIUrl":"10.1016/j.ijcip.2025.100788","url":null,"abstract":"<div><div>Ensuring the security of railway systems is crucial to protecting both passengers and infrastructure from the increasing threat of cyberattacks. As these threats grow in complexity and frequency, the need for resilient attack detection systems becomes more pressing.</div><div>This study tackles the challenge of attack detection in railway systems using machine learning techniques. By integrating Generative Adversarial Networks (GANs), Convolutional Neural Networks (CNNs), and Transfer Learning (TL), we enhance detection accuracy and develop a robust approach capable of identifying both known and emerging threats. Our methodology utilized the Electra Modbus dataset as the source domain and was transferred to the Electra S7Comm dataset as the target domain. Experimental results highlight the effectiveness of GAN-based data augmentation in mitigating the scarcity of attack samples, enhancing both the robustness and generalizability of our detection models. Additionally, the application of pre-trained models through transfer learning played a crucial role in achieving superior performance. Our proposed solution can be deployed within railway networks to strengthen security measures, enabling proactive responses to cyber threats, safeguarding critical infrastructure, and ensuring uninterrupted operations.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"50 ","pages":"Article 100788"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}