International Journal of Critical Infrastructure Protection最新文献

Securing Industrial Control Systems (ICS) against cyber threats is crucial for maintaining operational reliability and safety in critical infrastructure. Traditional Machine Learning (ML) approaches in ICS development require substantial domain expertise, posing challenges for non-experts. To address this gap, we propose and evaluate ICS-defender, a defense mechanism to enhance ICS security through Automated Machine Learning (AutoML) techniques. Our approach leverages sophisticated feature engineering and AutoML to automate model selection, training, aggregation, and optimization, thereby reducing the dependency on specialized knowledge. We evaluate ICS-defender against state-of-the-art AutoML frameworks using diverse datasets from power systems and electric vehicle chargers. Experimental results consistently demonstrate that ICS-defender outperforms existing frameworks in terms of accuracy and robustness, achieving average accuracies of 93.75%, 94.34%, and 87.12% for power systems attacks datasets and 94.23% for the electric vehicle charging station attacks dataset, surpassing baseline algorithms. This research contributes to advancing secure and resilient ICS, offering significant implications for broader applications and future enhancements in industrial cybersecurity.

Recently released scan data on Shodan reveals that thousands of Industrial Control Systems (ICSs) worldwide are directly accessible via the Internet and, thus, exposed to cyber-attacks aiming at financial gain, espionage, or disruption and/or sabotage. Executing sophisticated cyber–physical attacks aiming to manipulate industrial functionalities requires a deep understanding of the underlying physical process at the core of the target ICS, for instance, through unauthorized access to memory registers of Programmable Logic Controllers (PLCs). However, to date, countermeasures aiming at hindering the comprehension of physical processes remain largely unexplored.

In this work, we investigate the use of obfuscation strategies to complicate process comprehension of ICSs while preserving their runtime evolution. To this end, we propose a framework to design and evaluate obfuscation strategies for PLCs, involving PLC memory registers, PLC code (user program), and the introduction of extra (spurious) physical processes. Our framework categorizes obfuscation strategies based on two dimensions: the type of (spurious) registers employed in the obfuscation strategy and the dependence on the (genuine) physical process. To evaluate the efficacy of proposed obfuscation strategies, we introduce evaluation metrics to assess their potency and resilience, in terms of system invariants the attacker can derive, and their cost in terms of computational overhead due to runtime modifications of spurious PLC registers. We developed a prototype tool to automatize the devised obfuscation strategies and applied them to a non-trivial use case in the field of water tank systems. Our results show that code obfuscation can be effectively used to counter malicious process comprehension of ICSs achieved via scanning of PLC memory registers. To our knowledge, this is the first work using obfuscation as a technique to protect ICSs from such threats. The efficacy of the proposed obfuscation strategies predominantly depends on the intrinsic complexity of the interplay introduced between genuine and spurious registers.

The security of assets within electrical substations is paramount to ensuring the reliable and resilient operation of the energy sector. However, implementing existing industry cybersecurity standards in these environments presents numerous technical challenges. In this work, we provide systematic guidance that emphasizes best practices and prioritizes requirement implementation. We examine the application of Software-Defined Networking (SDN) as a means to enhance security within the IEC 62443 family of standards. Specifically, we offer insights into how the security measures required for compliance with the IEC 62443 security standards can impact the stringent timing constraints of contemporary communication protocols, enabling advanced distribution system operations in the future. Utilizing a testbed modeled after a real-world electrical substation, we demonstrate that while SDN-based security features naturally introduce some additional latency, their operational impact on the network’s strict constraints is minimal.

Among environmental facilities, wastewater treatment facilities have a crucial role in sustaining human life, and any occurrence of an earthquake or flood within these facilities can result in various social, economic, and environmental issues, either directly or indirectly. Therefore, a quantitative vulnerability assessment of wastewater treatment facilities is necessary to minimize and prevent damage from earthquakes and flood disasters. For this reason, this study introduces a novel indicator to assess the susceptibility of disasters, considering aspects of exposure, sensitivity, and adaptive capacity. The newly proposed indicator encompasses numerous evaluation criteria, topography, natural surroundings, hydraulic systems, structural composition, and non-structural features. Also, Weights derived using the combined weight calculation (CWC) method, which combined the analytic hierarchy process (AHP) and entropy weight method were applied to the indicator. It was tested across 23 cities to validate its efficacy, revealing a substantial correlation between the vulnerability index and the specific attributes of the city's wastewater treatment facilities. Therefore, this study analyzed wastewater treatment facilities by comparing the attributes of the urban areas under investigation, such as topological characteristics, urbanization levels, population density, infrastructure quality, and disaster preparedness resources available. The suggested methodology can facilitate the development of strategies aimed at averting damage caused by earthquakes or floods and reducing the adverse impact on wastewater treatment facilities while considering the unique characteristics of the urban setting in question.

This paper addresses the critical need for enhancing security in Supervisory Control and Data Acquisition (SCADA) networks within Industrial Control Systems (ICSs) to protect the industrial processes from cyber-attacks. The purpose of our work is to propose and evaluate lightweight security measures to safeguard critical infrastructure resources. The scope of our effort involves simulating a secure SCADA/IoT-based hardware test bench for ICSs, utilizing Modbus and MQTT communication protocols. Through case studies in remote servo motor control, water distribution systems, and power system voltage level indicators, vulnerabilities such as Denial of Service (DoS) and Man-in-The-Middle (MiTM) attacks are identified, and security recommendations are provided. To execute our work, we deploy lightweight ciphers such as Prime Counter & Hash Chaining (PCHC) and Ascon algorithm with Compression Rate (ACR) for secure information exchange between the plant floor and the control center. Evaluation of these ciphers on Raspberry Pi focuses on execution speed and memory utilization. Additionally, a comparison with the AGA-12 protocol standard for SCADA networks is conducted to underscore the efficacy of the proposed security measures. Our findings include the identification of SCADA network vulnerabilities and the proposal of lightweight security measures to mitigate risks. Performance evaluation of the proposed ciphers on Raspberry Pi demonstrates their effectiveness, emphasizing the importance of deploying such measures to ensure resilience against cyber threats in SCADA environments.

Urban Underground Logistics Systems (UULS) have become an emerging solution to mitigate urban surface traffic congestion, environmental pollution, and surface transport safety risks. However, during the operation of UULS, the use of advanced technologies such as the Internet of Things (IoT) introduces cybersecurity risks to the system. Moreover, severe natural disasters can also cause damage to underground transportation network links. Existing research and planning primarily concentrate on the system design and benefits of UULS, neglecting the system's service level under attack scenarios. This study outlines three representative UULS network prototypes and proposes a resilience quantification method centered on logistics efficiency. It also focuses on comparing the effectiveness of three recovery strategies. These strategies give priority to maximum flow, betweenness centrality, and regional importance, as well as the priority of node and link repairs. The resilience quantification method and recovery strategies are applied in a case study set in Nanjing City. The case study results reveal that the Two-echelon network shows exceptional resilience. Regarding the effectiveness of recovery strategies, the strategy based on maximum flow proves to be the most effective, and focusing on node repair can lead to higher system resilience. Based on these findings, this study offers recommendations to transportation and logistics management decision-makers, focusing on UULS resilience and recovery strategy selection. These recommendations are intended to provide valuable guidance for the planning and design of future UULS, ensuring their resilience and reliability.

The European Union is promoting cross-border electricity interconnection projects to achieve energy objectives, reduce the current fragmented European market, and eradicate the isolation of the most disadvantaged areas. However, selecting these projects is a complex task because there are multiple objectives, criteria, participants and alternatives involved. This paper aims to develop a multi-criteria decision analysis (MCDA) method for appropriately assessing and prioritizing cross-border electricity interconnection projects considering technical, economic, environmental and social criteria. Additionally, this work analyzes interconnection effects on the resilience of interconnected power systems. To verify its validity, this method is applied to prioritize new Spain-France interconnection infrastructure projects. From the results obtained, the technical and environmental criteria have proven to be the most important, since cross-border electricity interconnection projects are aimed at better market-coupling, less congestion and higher reliability while minimizing environmental impacts. In short, the proposed methodology provides a comprehensive view of the impact of these projects.

The cyber-attack on the Ukrainian positioning network at the beginning of the ongoing Russia-Ukraine war demonstrated how the branching of satellite connections can have severe repercussions for communication systems. While ground-based networks are changing, the vulnerability of critical infrastructure to cyber-attacks and technical failures has become a serious concern. As cyber attackers are increasingly targeting industrial control systems rather than stealing data, attacks have become more sophisticated and significant. Future connectivity to 5 G networks, the entry of new private players in this sector, and the economic growth of emerging countries will further increase the attack surface of the space sector. A risk-based approach is therefore needed to increase protection and resilience against cyber-attacks. This requires a comprehensive understanding of the technologies and their vulnerabilities, as well as the ability to quickly develop solutions to counter attacks. Responding effectively with legal and policy means is essential to adapting to changes and to providing continuity and security of services. This paper highlights the main qualities of communication technology, its vulnerabilities, and the critical challenges to achieving cyber resilience. It identifies significant assets, defence solutions, and legal and policy aspects that should be further researched to enhance the cyber resilience of European assets.