International Journal of Critical Infrastructure Protection最新文献

{"title":"OptAML: Optimized adversarial machine learning on water treatment and distribution systems","authors":"Mustafa Sinasi Ayas ,&nbsp;Enis Kara ,&nbsp;Selen Ayas ,&nbsp;Ali Kivanc Sahin","doi":"10.1016/j.ijcip.2025.100740","DOIUrl":"10.1016/j.ijcip.2025.100740","url":null,"abstract":"<div><div>This research presents the optimized adversarial machine learning framework, OptAML, which is developed for use in water distribution and treatment systems. In consideration of the physical invariants of these systems, the OptAML generates adversarial samples capable of deceiving a hybrid convolutional neural network-long short-term memory network model. The efficacy of the framework is assessed using the Secure Water Treatment (SWaT) and Water Distribution (WADI) datasets. The findings demonstrate that OptAML is capable of effectively evading rule checkers and significantly reducing the accuracy of anomaly detection frameworks in both systems. Additionally, the study investigates a defense mechanism that demonstrates enhanced robustness against these adversarial attacks and is based on adversarial training. Our results underscore the necessity for robust and flexible protection tactics and highlight the shortcomings of the machine learning-based anomaly detection systems for critical infrastructure that are currently in place.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"48 ","pages":"Article 100740"},"PeriodicalIF":4.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167952","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":"Artificial immunity-based energy theft detection for advanced metering infrastructures","authors":"Jie Fu ,&nbsp;Chengxi Yang ,&nbsp;Yuxuan Liu ,&nbsp;Kunsan Zhang ,&nbsp;Jiaqi Li ,&nbsp;Beibei Li","doi":"10.1016/j.ijcip.2025.100739","DOIUrl":"10.1016/j.ijcip.2025.100739","url":null,"abstract":"<div><div>Advanced Metering Infrastructure (AMI) is envisioned to enable smart energy management and consumption while ensuring the integrity of real energy consumption data. However, existing smart meters, gateways, and communication channels are usually weakly protected, often opening a huge door for data eavesdroppers who may be easily to further construct energy thefts. Although some energy theft detection schemes have already been reported in the literature, they often fail to take into account the dense data distribution characteristics of energy consumption data, resulting in compromised detection performance. To this end, we in this paper propose a novel ar<strong>T</strong>ificial <strong>IM</strong>mune based <strong>E</strong>nergy theft <strong>D</strong>etection (TIMED) scheme, which can effectively identify five types of energy thefts. Specifically, we first develop an energy consumption data pre-processing method, which can effectively reduce the dimensionality of raw energy consumption data to facilitate the data analyzing efficiency. Second, we design a center-distance-based energy theft detector generation method to create high-quality detectors with low elimination rates. Last, we devise a nonself-based hole repair method for energy theft detectors, which can further reduce the false negative alarms. Extensive experiments on a real public AMI dataset demonstrate that the proposed TIMED scheme is highly effective in identifying pulse attacks, scaling attacks, ramping attacks, random attacks, and smooth-curve attacks. The results show that TIMED outperforms many existing machine learning and traditional artificial immunity-based energy theft detection methods.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"48 ","pages":"Article 100739"},"PeriodicalIF":4.1,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167950","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":"An efficient convolutional neural network based attack detection for smart grid in 5G-IOT","authors":"Sheeja Rani S ,&nbsp;Mostafa F. Shaaban ,&nbsp;Abdelfatah Ali","doi":"10.1016/j.ijcip.2024.100738","DOIUrl":"10.1016/j.ijcip.2024.100738","url":null,"abstract":"<div><div>The deployment of 5G networks and IoT devices in smart grid applications provides electricity-generated, distributed, and managed bidirectional transmission of real-time information between utility providers and consumers. However, this increased transmission and confidence in IoT devices also present novel security challenges, since they are vulnerable to malicious attacks. Ensuring robust attack detection mechanisms in 5G-IoT smart grid systems for reliable and efficient power distribution, and early accurate identification of attacks addressed. To solve these concerns, a novel technique called Target Projection Regressed Gradient Convolutional Neural Network (TPRGCNN) is introduced to improve the accuracy of attack detection during data transmission in a 5G-IoT smart grid environment. The TPRGCNN method is combined with feature selection and classification for improving secure data transmission by detecting attacks in 5G-IoT smart grid networks. In the feature selection process, TPRGCNN utilizes the Ruzicka coefficient Dichotonic projection regression method and aims to enhance the accuracy of attack detection while minimizing time complexity. Then selected significant features are fed into Jaspen’s correlative stochastic gradient convolutional neural learning classifier for attack detection. Classification indicates whether transmission is normal or an attack in the 5G-IoT smart grid network. The implementation results demonstrate that the proposed TPRGCNN method achieve a 5% of improved attack detection accuracy and 2% improvement in precision, recall, F-score while reducing time complexity and space complexity by 13% and 23% compared to conventional methods.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"48 ","pages":"Article 100738"},"PeriodicalIF":4.1,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167951","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":"CABBA: Compatible Authenticated Bandwidth-efficient Broadcast protocol for ADS-B","authors":"Mikaëla Ngamboé ,&nbsp;Xiao Niu ,&nbsp;Benoit Joly ,&nbsp;Steven P. Biegler ,&nbsp;Paul Berthier ,&nbsp;Rémi Benito ,&nbsp;Greg Rice ,&nbsp;José M. Fernandez ,&nbsp;Gabriela Nicolescu","doi":"10.1016/j.ijcip.2024.100728","DOIUrl":"10.1016/j.ijcip.2024.100728","url":null,"abstract":"<div><div>The Automatic Dependent Surveillance-Broadcast (ADS-B) is a surveillance technology mandated in many airspaces. It improves safety, increases efficiency and reduces air traffic congestion by broadcasting aircraft navigation data. Yet, ADS-B is vulnerable to spoofing attacks as it lacks mechanisms to ensure the integrity and authenticity of the data being supplied. None of the existing cryptographic solutions fully meet the backward compatibility and bandwidth preservation requirements of the standard. Hence, we propose the Compatible Authenticated Bandwidth-efficient Broadcast protocol for ADS-B (CABBA), an improved approach that integrates TESLA, phase-overlay modulation techniques and certificate-based PKI. As a result, entity authentication, data origin authentication, and data integrity are the security services that CABBA offers. To assess compliance with the standard, we designed an SDR-based implementation of CABBA and performed backward compatibility tests on commercial and general aviation (GA) ADS-B in receivers. Besides, we calculated the 1090ES band’s activity factor and analyzed the channel occupancy rate according to ITU-R SM.2256-1 recommendation. Also, we performed a bit error rate analysis of CABBA messages. The results suggest that CABBA is backward compatible, does not incur significant communication overhead, and has an error rate that is acceptable for Eb/No values above 14 dB.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"48 ","pages":"Article 100728"},"PeriodicalIF":4.1,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond botnets: Autonomous Firmware Zombie Attack in industrial control systems","authors":"Seyed Ali Alavi,&nbsp;Hamed Pourvali Moghadam,&nbsp;Amir Hossein Jahangir","doi":"10.1016/j.ijcip.2024.100729","DOIUrl":"10.1016/j.ijcip.2024.100729","url":null,"abstract":"<div><div>This paper introduces a novel cyberattack vector called the ”Autonomous Firmware Zombie Attack.” Unlike traditional zombie attacks that rely on botnets and direct network control, this method enables attackers to covertly modify the firmware of substation Intelligent Electronic Devices (IEDs) and other firmware-based appliances, including critical industrial equipment, without requiring an active network connection, leaving minimal trace and making an offensive attack with only one infected device instead of a set of multiple devices in botnets. Unlike conventional cyber threats, this method allows attackers to manipulate devices to cause substantial damage while leaving minimal trace, thus evading traditional detection techniques. This study demonstrates the potential of the Autonomous Firmware Zombie Attack (AFZA), which causes substantial damage while evading conventional detection techniques. We first run such an attack on a series of IEDs as proof of concept for this issue. Then, we compare this approach to traditional remote control attacks, highlighting its unique advantages and implications for industrial control system security. This research underscores the critical need for a robust cybersecurity framework tailored to industrial control systems and advances our understanding of the complex risk landscape threatening critical infrastructures.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"48 ","pages":"Article 100729"},"PeriodicalIF":4.1,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167813","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":"Simulation of multi-stage attack and defense mechanisms in smart grids","authors":"Ömer Sen ,&nbsp;Bozhidar Ivanov ,&nbsp;Christian Kloos ,&nbsp;Christoph Zöll ,&nbsp;Philipp Lutat ,&nbsp;Martin Henze ,&nbsp;Andreas Ulbig ,&nbsp;Michael Andres","doi":"10.1016/j.ijcip.2024.100727","DOIUrl":"10.1016/j.ijcip.2024.100727","url":null,"abstract":"<div><div>The power grid is a vital infrastructure in modern society, essential for ensuring public safety and welfare. As it increasingly relies on digital technologies for its operation, it becomes more vulnerable to sophisticated cyber threats. These threats, if successful, could disrupt the grid’s functionality, leading to severe consequences. To mitigate these risks, it is crucial to develop effective protective measures, such as intrusion detection systems and decision support systems, that can detect and respond to cyber attacks. Machine learning methods have shown great promise in this area, but their effectiveness is often limited by the scarcity of high-quality data, primarily due to confidentiality and access issues.</div><div>In response to this challenge, our work introduces an advanced simulation environment that replicates the power grid’s infrastructure and communication behavior. This environment enables the simulation of complex, multi-stage cyber attacks and defensive mechanisms, using attack trees to map the attacker’s steps and a game-theoretic approach to model the defender’s response strategies. The primary goal of this simulation framework is to generate a diverse range of realistic attack data that can be used to train machine learning algorithms for detecting and mitigating cyber attacks. Additionally, the environment supports the evaluation of new security technologies, including advanced decision support systems, by providing a controlled and flexible testing platform.</div><div>Our simulation environment is designed to be modular and scalable, supporting the integration of new use cases and attack scenarios without relying heavily on external components. It enables the entire process of scenario generation, data modeling, data point mapping, and power flow simulation, along with the depiction of communication traffic, in a coherent process chain. This ensures that all relevant data needed for cyber security investigations, including the interactions between attacker and defender, are captured under consistent conditions and constraints.</div><div>The simulation environment also includes a detailed modeling of communication protocols and grid operation management, providing insights into how attacks propagate through the network. The generated data are validated through laboratory tests, ensuring that the simulation reflects real-world conditions. These datasets are used to train machine learning models for intrusion detection and evaluate their performance, specifically focusing on how well they can detect complex attack patterns in power grid operations.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"48 ","pages":"Article 100727"},"PeriodicalIF":4.1,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical threats vs Cyber threats","authors":"Roberto Setola","doi":"10.1016/S1874-5482(24)00075-1","DOIUrl":"10.1016/S1874-5482(24)00075-1","url":null,"abstract":"","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"47 ","pages":"Article 100734"},"PeriodicalIF":4.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154825","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":"Optimized unmanned aerial vehicle pathway system in disaster resilience network","authors":"Yi-Wei Ma,&nbsp;Desti Syuhada","doi":"10.1016/j.ijcip.2024.100726","DOIUrl":"10.1016/j.ijcip.2024.100726","url":null,"abstract":"<div><div>After a disaster, the interruption of networks in affected areas is a significant challenge, exacerbated by the malfunction of base stations and the complete absence of network infrastructure. Hence, the objective of this study is to achieve a systematic and well-supported path in the post-disaster system through the optimization of coverage area and the provision of high-quality service. Therefore, this study aims to enhance the extent of coverage and transmission efficiency by considering the specific needs of users to establish a logical and systematic flight path of Unmanned Aerial Vehicles (UAVs) in a post-disaster scenario. This study demonstrates a 12.7 % availability advantage over random methods that do not consider users and only generalize cluster length. This study optimizes the performance of the UAV by adjusting its altitude position best to meet the requirements of its coverage and transmission quality.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"47 ","pages":"Article 100726"},"PeriodicalIF":4.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748486","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":"FingerCI: Writing industrial process specifications from network traffic","authors":"Filipe Apolinário ,&nbsp;Nelson Escravana ,&nbsp;Éric Hervé ,&nbsp;Miguel L. Pardal ,&nbsp;Miguel Correia","doi":"10.1016/j.ijcip.2024.100725","DOIUrl":"10.1016/j.ijcip.2024.100725","url":null,"abstract":"<div><div>Critical infrastructures (CIs) are often targets of cyber-attacks, requiring accurate process specifications to identify and defend against incidents. However, discrepancies between these specifications and real-world CI conditions arise due to the costly process of manual specification by experts.</div><div>This paper introduces <span>FingerCI</span>, a method for automatically generating CI process specifications through network traffic analysis and physical behavior modeling. By defining a Specification Language that integrates with existing systems, <span>FingerCI</span> extracts industrial process specifications without infrastructure changes or downtime. The specifications include a behavior model that validates physical correctness.</div><div>We evaluated <span>FingerCI</span> on a digital twin of an airport baggage handling system, achieving 99.98% fitness to observed behavior. Our method improves cybersecurity and fault detection with high accuracy.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"47 ","pages":"Article 100725"},"PeriodicalIF":4.1,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703044","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":"Space cybersecurity challenges, mitigation techniques, anticipated readiness, and future directions","authors":"Shah Khalid Khan ,&nbsp;Nirajan Shiwakoti ,&nbsp;Abebe Diro ,&nbsp;Alemayehu Molla ,&nbsp;Iqbal Gondal ,&nbsp;Matthew Warren","doi":"10.1016/j.ijcip.2024.100724","DOIUrl":"10.1016/j.ijcip.2024.100724","url":null,"abstract":"<div><div>Space Cybersecurity (SC) is becoming critical due to the essential role of space in global critical infrastructure – enabling communication, safe air travel, maritime trade, weather monitoring, environmental surveillance, financial services, and defence systems. Simultaneously, involving diverse stakeholders in space operations further amplifies this criticality. Similarly, previous research has identified isolated vulnerabilities in SC and proposed individual solutions to mitigate them. While such studies have provided useful insights, they do not offer a comprehensive analysis of space cyber-attack vectors and a critical evaluation of the effectiveness of mitigation strategies. This study addresses this problem by holistically examining the scope of potential space cyber-attack vectors, encompassing the ground, space, user, cloud, communication channels, and supply chain segments. Furthermore, the study evaluates the effectiveness of legacy security controls and frameworks and outlines SC-vector-aligned counterstrategies and mitigation techniques to tackle the unique SC threats. Based on the analysis, the study proposes future research directions to develop and test advanced technological solutions and regulatory and operational frameworks to establish international standards policies and foster stakeholder collaboration. The study contributes a multi-disciplinary foundation and roadmap that researchers, technology developers, and decision-makers can draw on in shaping a robust and sustainable SC framework.</div></div>","PeriodicalId":49057,"journal":{"name":"International Journal of Critical Infrastructure Protection","volume":"47 ","pages":"Article 100724"},"PeriodicalIF":4.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}