Data Governance to Counter Hybrid Threats against Critical Infrastructures
Highlights
- Hybrid threats exploit vulnerabilities in digital infrastructure to undermine trust in democratic systems and security, mainly targeting critical infrastructure (CI).
- Data governance in countering hybrid attacks can help establish accountability, verifiability, and ownership frameworks for digital information dissemination during emergencies.
- Integrating data governance with business process management enhances response awareness, preemptive security escalation, and comprehensive logging for non-repudiation, supporting response efforts and mitigating cascading effects in CI attacks.
- The synergy of proactive strategies and the information security lifecycle protects digital assets through detection, prevention, response, and knowledge management for incident mitigation.
- Implementing robust data governance frameworks strengthens Resilience against hybrid threats, promotes trusted information exchange, and facilitates stakeholder collaboration for effective emergency response in critical infrastructures like airports.
- Enhanced Resilience: data governance frameworks enhance CI resilience against hybrid threats by establishing accountability, ensuring data integrity, and facilitating prompt response awareness.
- Improved Response Coordination: integrating data governance with business process management enables effective response coordination, preemptive security escalation, and comprehensive logging for non-repudiation, mitigating cascading effects in CI attacks.
- Stakeholder Collaboration: findings underscore the importance of collaboration among airport authorities, airlines, security agencies, and other stakeholders to ensure the integrity and authenticity of exchanged information during emergencies.
- Proactive Security Measures: the paper emphasizes proactive security measures, such as encryption, access controls, and lineage tracking, to safeguard data integrity and prevent unauthorized modifications, strengthening defenses against hybrid attacks.
- Informed Decision-Making: data governance frameworks ensure data protection, accuracy, and integrity, allowing decision-makers to make informed decisions, maintain data reliability, and address risks associated with inaccurate information or data mishandling, enhancing CI's overall security posture.
Abstract
:1. Introduction
- Implementing robust frameworks enhances resilience against hybrid threats. Integrating data governance frameworks with Infosec practices enables organizations to improve data security, access controls, and incident response procedures. This integration enhances breach detection, aids in identifying attackers, and serves as an effective countermeasure. The structured approach strengthens the organization’s capability to withstand and recover from cyber-attacks and other malicious activities, thereby boosting overall resilience.
- Establishing trusted information exchanges and promoting stakeholder collaboration for an emergency response necessitates securing information exchange with external parties, including organizations from the tourism and logistics sectors, regulatory bodies, and emergency response teams. Implementing secure data-sharing protocols and fostering collaboration enables airports to enhance their emergency response capabilities and improve coordination to address security incidents.
- Integrating data governance with Infosec strengthens security measures by combining data protection protocols with proactive monitoring and threat mitigation strategies. This approach allows airports to detect and respond to real-time security incidents, preemptively address potential threats, and safeguard critical infrastructures from cyber-attacks and other malicious activities. These principles underscore this study’s focus on harmonizing data governance practices with Infosec strategies to strengthen the security posture of critical infrastructures and improve emergency response capabilities in the face of evolving cyber threats.
2. Nature of a Hybrid Attack for the Case of Critical Infrastructures
- Cyber–physical infrastructure vulnerability: malicious actors gain unauthorized access to the airport’s computer systems, including those managing flight scheduling, baggage handling, and air traffic control.
- -
- Exploitation: a cyber intrusion might disrupt flight operations, leading to flight delays, cancellations, or misdirections. Simultaneously, physical sabotage can target the components of a critical infrastructure, such as power supply systems or communication networks.
- -
- Consequence: the combined cyber–physical attack results in chaotic airport operations, potentially compromising passenger safety, causing economic losses, and undermining public trust in airport security measures.
- Insider threats exploiting operational gaps: an insider with access to sensitive airport information collaborates with external threat actors.
- -
- Exploitation: the insider provides information, access credentials, or physical access to critical areas to external actors, facilitating unauthorized access or tampering with airport systems.
- -
- Consequence: this collaboration allows hybrid attackers to bypass conventional security measures, potentially leading to disruptions, theft, or damage to airport infrastructures. Insider involvement complicates threat detection and attribution, making mitigation and effective responses more challenging.
- Supply chain vulnerability: airport procurement processes are compromised, allowing malicious actors to introduce compromised components or software into airport systems.
- -
- Exploitation: malicious actors infiltrate the airport’s supply chain, introducing malware-infected equipment or compromised software during procurement or maintenance activities.
- -
- Consequence: the compromised components or software create backdoors or vulnerabilities within airport systems, allowing attackers to exploit weaknesses, disrupt operations, or exfiltrate sensitive data. Supply chain compromises may remain undetected for extended periods, posing significant challenges for incident response and recovery efforts.
- Dimension 1: a disinformation campaign targeting European borders, promoting ideological extremism and violence, commencing in Month 1, with a duration of x time units.
- Dimension 2: attack on critical infrastructures like airports or renewable energy facilities, leading to supply chain disruptions, beginning in Month 2, with a duration of y time units.
- Dimension 3: foreign investments in critical entities, starting in Month 3, with a duration of z time units.
3. Results Addressing the Governance of the Digital Information Landscape
3.1. Digital Information Security Framework
3.1.1. Prevent—Sets the Groundwork
3.1.2. Detect—Identifies Security Incidents
3.1.3. Response—Addresses Incidents in Real-Time
3.1.4. Knowledge Management—Ensures Ongoing Resilience and Improvement
3.2. Application of Data Governance for the Response Phase
4. Discussion
4.1. Social, Environmental, and Other Impacts
4.2. Prevention of Cascading Effects
4.3. Case Study
- In a real-world scenario, airports have utilized IoCs to prevent hybrid threats by identifying malicious activities early. For instance, during a cyberattack on an airport’s baggage handling system, the Infosec Dashboard detected unusual network traffic patterns and unauthorized access attempts, which are typical IoCs. By analyzing these indicators, the security team identified a malware infection attempting to disrupt operations. Swiftly isolating affected systems and implementing containment measures prevented widespread disruption. The Infosec Dashboard provided real-time alerts and detailed reports, enabling the team to trace the malware’s origin and block similar future attacks, thus safeguarding the airport’s critical infrastructure. As explained in Figure 4, external stakeholders are notified of the incident (A.6.8) and receive information to prevent supply chain disruptions, which are cascading effects.
- Similarly, IoAs have been employed to mitigate threats by focusing on the methods and tactics used by attackers. When an airport faced a coordinated physical and cyberattack, the Infosec Dashboard identified IoAs, such as repeated failed login attempts, phishing emails targeting airport staff, and unusual user behavior patterns. These indicators highlighted an impending attack, prompting the airport’s security team to activate incident response plans. Enhanced physical security measures and immediate cybersecurity protocols, such as enforcing multi-factor authentication and conducting staff training on recognizing phishing attempts, were implemented. This proactive approach, guided by IoAs, enabled the airport to thwart the attack, ensuring passenger safety and operational continuity.
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A. BPMN Core Elements and Symbols
Symbol | Description |
---|---|
Event | An event (represented by a circle) is something that “happens” during the course of a business process. An event affects the flow of the process and usually has a cause (trigger) or an impact (result). Event markers are circles with open centers to represent different actions (triggers or results). There are three types of events, based on when they affect the flow: Start, Intermediate, and End. Start events can only react to a response (“catch”) to a trigger (incoming action/input). Intermediate events can catch or throw triggers. For events that catch, the markers are unfilled, and for events that throw, the markers are filled. End events can react to sending (“throw”) a trigger (outgoing result/output) from a sequence flow path ending. |
Activity | An activity, represented by a rounded-corner rectangle, encompasses generic work to be performed, with two types: a standard activity and a subprocess (identified with a plus sign). Activities with a subprocess marker behave like normal processes once instantiated. They encapsulate processes modeled by activities, gateways, events, and sequence flows. Subprocesses allow complex processes to be split into levels, focusing on specific areas in a single diagram. The business rule activity interfaces with a business rule engine, facilitating input and output exchanges. Loop-marked activities serve as wrappers for inner activities executed multiple times. A call activity references an externally defined activity, fostering reusable process definitions across various processes. Flow objects connected by sequence flows (solid lines with arrowheads) structure business processes in diagrams. Activities can also link to data stores (represented by cylinders) for persistent data. A data store is somewhere where the process can read or write data that persist beyond the process’s scope. |
Gateway | A gateway, depicted as a diamond shape, controls the divergence and convergence of sequence flows, influencing traditional decisions and managing forking and merging path joining. Internal markers denote behavior control types. A diverging Exclusive Gateway (XOR Decision) creates alternative paths in a process flow, where only one path is taken for a given instance. In contrast, a diverging Inclusive Gateway (OR Decision) allows multiple paths with true evaluations, considering each as independent. Default paths, marked by “/”, ensure at least one path is taken if no valid conditions exist. An event-based gateway signifies a process branching point where alternative paths depend on events rather than condition expressions. A specific event, typically a message receipt, determines the chosen path. |
Pool | A pool is the graphical representation of a participant (e.g., stakeholder). It also acts as a “swimlane” and a graphical container for partitioning a set of activities from other pools, usually in the context of B2B situations. A pool can have internal details (whitebox pool) in the process that will be executed, or a pool can have no internal information (blackbox pool) used to model an external participant. Lanes describe who executes a specific set of activities, meaning that a lane represents sub-entities that appear inside the pool lane. A BPMN diagram can contain one or more pools, with all the other objects placed in each lane of the process pool. |
Appendix B. Examples of Indicators of Compromise
Unusual network traffic patterns: sudden increases in network traffic or unexpected outbound connections to unknown IP addresses. | |
Automated response: trigger alerts, block suspicious outbound connections, and initiate packet captures for further analyses. Reactive responses:
| |
Unauthorized access attempts: multiple failed login attempts or access from unexpected geographic locations. | |
Automated response: lock affected user accounts, alert security personnel, and log all attempts for forensic analyses. Reactive responses:
| |
Malware detection: detection of malware signatures on critical systems or endpoints within the airport network. | |
Automated response: isolate infected systems, initiate automated malware-removal procedures, and conduct a network-wide scan for further infections. Reactive responses:
| |
Unapproved configuration changes: unauthorized changes to system configurations, firewall settings, or security policies. | |
Automated response: rollback unauthorized changes, alert IT administrators, and perform an audit to identify the source of the change. Reactive responses:
| |
Data exfiltration indicators: large volumes of data being transferred to external locations or unusual data access patterns. | |
Automated response: halt data transfers, alert data protection officers, and implement data loss prevention measures to prevent further exfiltration. Reactive responses:
|
- Implement automated threat detection systems: This recommendation deploys advanced intrusion detection systems, security information, and event management solutions to automatically detect and alert security teams to potential intrusions and IoCs. For example, it is used to monitor network traffic for anomalies, such as unexpected outgoing connections to suspicious domains or unusual patterns in data transfer rates.
- Unauthorized access attempts: security plans can provide step-by-step responses to handle unauthorized access.
- Unapproved configuration changes: security plans can detail the actions to revert unauthorized changes and secure configurations.
- Data exfiltration indicators: security plans can guide data exfiltration incidents’ containment and investigation processes.
- Establish incident response playbooks: Develop comprehensive security plans tailored to airport infrastructure threats. These playbooks should outline step-by-step procedures for identifying, containing, and mitigating security incidents, including procedures for addressing common IoCs. For instance, the security plan could include predefined actions for responding to indicators such as unauthorized access attempts, malware infections, or unusual network activity.
- Unauthorized access attempts: security plans can provide step-by-step responses to handle unauthorized access.
- Unapproved configuration changes: security plans can detail the actions to revert unauthorized changes and secure configurations.
- Data exfiltration indicators: security plans can guide the containment and investigation processes for data exfiltration incidents.
- Enhance cross-agency collaboration: Foster collaboration and information sharing between airport security teams, law enforcement agencies, and relevant government organizations to ensure a coordinated response to security threats. Establishing real-time channels for sharing threat intelligence and IoC data can enable faster detections and responses to security incidents. For example, sharing IoCs such as suspicious IP addresses, domain names associated with phishing campaigns, or malware signatures can help identify and neutralize threats more effectively across airport infrastructures.
- Unusual network traffic patterns: collaboration can help identify whether unusual patterns are part of a larger attack affecting multiple agencies.
- Unauthorized access attempts: sharing information about access attempts can help other agencies recognize and defend against similar attempts.
- Malware detection: collaborative efforts can lead to the quicker identification and mitigation of widespread malware threats.
- Data exfiltration indicators: coordinated responses can help track and prevent data exfiltration across interconnected systems and agencies.
References
- Sendjaja, T.; Irwandi; Prastiawan, E.; Suryani, Y.; Fatmawati, E. Cybersecurity in the Digital Age: Developing Robust Strategies to Protect against Evolving Global Digital Threats and Cyber Attacks. Int. J. Sci. Soc. 2024, 6, 1008–1019. [Google Scholar] [CrossRef]
- Savolainen, J. Hybrid Threats and Vulnerabilities of Modern Critical Infrastructure—Weapons of Mass Disturbance (WMDi)? Hybrid CoE—The European Centre of Excellence for Countering Hybrid Threats: Helsinki, Finland, 2019. [Google Scholar]
- European Commission. EU-HYBNET—Empowering a Pan-European Network to Counter Hybrid Threats. Grant Agreement No. 883054. 2020. Available online: https://euhybnet.eu/ (accessed on 24 May 2024).
- Cullen, P.; Juola, C.; Karagiannis, G.; Kivisoo, K.; Normark, M.; Rácz, A.; Schmid, J.; Schroefl, J. The Landscape of Hybrid Threats: A Conceptual Model (Public Version); Giannopoulos, G., Smith, H., Theocharidou, M., Eds.; EUR 30585 EN; Publications Office of the European Union: Luxembourg, 2021; ISBN 978-92-76-56943-5. [Google Scholar] [CrossRef]
- Arădăvoaicei, I.A.; Bănacu, C.-S.; Andreica, M.; Ivan, L. Composite Indicators Used in Measuring Hybrid Threats. Proc. Int. Conf. Bus. Excell. 2023, 17, 882–894. [Google Scholar] [CrossRef]
- Jungwirth, R.; Smith, H.; Willkomm, E.; Savolainen, J.; Alonso Villota, M.; Lebrun, M.; Aho, A.; Giannopoulos, G. Hybrid Threats: A Comprehensive Resilience Ecosystem; EUR 31104 EN; Publications Office of the European Union: Luxembourg, 2023; ISBN 978-92-76-53292-7. [Google Scholar] [CrossRef]
- ISO/IEC 19510-2013; Information technology—Object Management Group Business Process Model and Notation. International Organization for Standardization: Geneva, Switzerland, 2013.
- ISO/IEC 21839-2019; International Standard—Systems and Software Engineering—System of Systems (SoS) Considerations in Life Cycle Stages of a System. International Organization for Standardization: Geneva, Switzerland, 2019.
- Koroniotis, N.; Moustafa, N.; Schiliro, F.; Gauravaram, P.; Janicke, H. A Holistic Review of Cybersecurity and Reliability Perspectives in Smart Airports. IEEE Access 2020, 8, 209802–209834. [Google Scholar] [CrossRef]
- Ukwandu, E.; Ben-Farah, M.A.; Hindy, H.; Bures, M.; Atkinson, R.; Tachtatzis, C.; Andonovic, I.; Bellekens, X. Cyber-Security Challenges in Aviation Industry: A Review of Current and Future Trends. Information 2022, 13, 146. [Google Scholar] [CrossRef]
- Habler, E.; Bitton, R.; Shabtai, A. Assessing Aircraft Security: A Comprehensive Survey and Methodology for Evaluation. ACM Comput. Surv. 2023, 56, 1–40. [Google Scholar] [CrossRef]
- Köpke, C.; Srivastava, K.; König, L.; Miller, N.; Fehling-Kaschek, M.; Burke, K.; Mangini, M.; Praça, I.; Canito, A.; Carvalho, O.; et al. Impact Propagation in Airport Systems. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Springer International Publishing: Berlin, Germany, 2021; Volume 12618, pp. 191–206. [Google Scholar]
- Ullah, F.; Edwards, M.; Ramdhany, R.; Chitchyan, R.; Babar, M.A.; Rashid, A. Data exfiltration: A review of external attack vectors and countermeasures. J. Netw. Comput. Appl. 2018, 101, 18–54. [Google Scholar] [CrossRef]
- King, J.; Bendiab, G.; Savage, N.; Shiaeles, S. Data exfiltration: Methods and detection countermeasures. In Proceedings of the 2021 IEEE International Conference on Cyber Security and Resilience, CSR 2021, Rhodes, Greece, 26–28 July 2021; pp. 442–447. [Google Scholar]
- Chen, Y.; Al-Rubaye, S.; Tsourdos, A.; Baker, L.; Gillingham, C. Differentially-Private Federated Intrusion Detection via Knowledge Distillation in Third-party IoT Systems of Smart Airports. In Proceedings of the IEEE International Conference on Communications, Rome, Italy, 28 May–1 June 2023; pp. 603–608. [Google Scholar]
- Nenad, N.; Kirkova, R. The concept of hybrid threats. Knowl. Int. J. 2018, 28, 1795–1799. [Google Scholar] [CrossRef]
- Sofou, S.; Pickl, S.; Pham, S.; Alonso, M.; Perlepes, L.; Kostaridis, A. Innovations to counter Hybrid Threats, the Case of Critical Infrastructures. In The Second ECSCI Workshop on Critical Infrastructure Protection and Resilience; European Commission: Brussels, Belgium; Luxembourg, 2022; pp. 96–100. [Google Scholar]
- Abraham, R.; Schneider, J.; vom Brocke, J. Data governance: A conceptual framework, structured review, and research agenda. Int. J. Inf. Manag. 2019, 49, 424–438. [Google Scholar] [CrossRef]
- Rascao, J.P. Data Governance in the Digital Age; IGI Global: Hershey, PA, USA, 2021; pp. 34–62. [Google Scholar]
- Micheli, M.; Ponti, M.; Craglia, M.; Suman, A.B. Emerging models of data governance in the age of datafication. Big Data Soc. 2020, 7, 2053951720948087. [Google Scholar] [CrossRef]
- Pestana, G.F.; Carvalho, L.M.; Gouveia-Carvalho, J.; Antunes, W. Digital Chain of Custody for CBRNE Events: Custody Transfer Governance. In Lecture Notes in Networks and Systems; Springer International Publishing: Cham, Switzerland, 2022; Volume 469, pp. 304–314. [Google Scholar]
- Shivhare, K. Business Process Modeling and Challenges through Examples. In Proceedings of the 17th Innovations in Software Engineering Conference, Bangalore, India, 22–24 February 2024. [Google Scholar] [CrossRef]
- Wagner, G. Business process modelling and simulation with dpmn, anylogic and simio—A tutorial. In Proceedings of the 11th Simulation Workshop, SW 2023, Southhamption, UK, 27–29 March 2023; pp. 22–36. [Google Scholar]
- O’Connor, J.; Eberle, C.; Cotti, D.; Hagenlocher, M.; Hassel, J.; Janzen, S.; Narvaez, L.; Newsom, A.; Ortiz-Vargas, A.; Schuetze, S.; et al. Interconnected Disaster Risks 2020. United Nations Univ. Inst. Environ. Hum. Secur. 2021, 60, 1–64. [Google Scholar]
- Urlainis, A.; Shohet, I.M.; Levy, R.; Ornai, D.; Vilnay, O. Damage in Critical Infrastructures Due to Natural and Manmade Extreme Events—A Critical Review. Procedia Eng. 2014, 85, 529–535. [Google Scholar] [CrossRef]
- Palleti, V.R.; Adepu, S.; Mishra, V.K.; Mathur, A. Cascading effects of cyber-attacks on interconnected critical infrastructure. Cybersecurity 2021, 4, 8. [Google Scholar] [CrossRef]
- European Parliament and the Council of the European Union. Directive 2022/2555 on Measures for a High Common Level of Cybersecurity across the Union. Off. J. Eur. Union. L 333/80. 2022. Available online: https://eur-lex.europa.eu/eli/dir/2022/2555/oj (accessed on 15 July 2024).
- Rinaldy, S.M.; Peerenboom, J.P.; Kelly, T.K. Identifying, Understanding, and Analyzing Critical Infrastructure Interdepend-encies. IEEE Control Syst. Mag. 2002, 21, 11–25. [Google Scholar]
- Suo, W.; Zhang, J.; Sun, X. Risk assessment of critical infrastructures in a complex interdependent scenario: A four-stage hybrid decision support approach. Saf. Sci. 2019, 120, 692–705. [Google Scholar] [CrossRef]
- Šarūnienė, I.; Martišauskas, L.; Krikštolaitis, R.; Augutis, J.; Setola, R. Risk Assessment of Critical Infrastructures: A Methodology Based on Criticality of Infrastructure Elements. Reliab. Eng. Syst. Saf. 2024, 243, 109797. [Google Scholar] [CrossRef]
Type | Examples of the Types of Data Exfiltration |
---|---|
Social engineering and phishing attacks | Social engineering and phishing deceive individuals into downloading malware or revealing account credentials. In social engineering, it may unknowingly surrender sensitive data or compromise security. Phishing emails mimic legitimate sources, luring recipients into clicking malicious attachments or entering credentials on spoofed websites, enabling malware injection or credential theft. |
Outbound emails | Cybercriminals use emails to exfiltrate any data that sit on organizations’ outbound email systems, such as calendars, databases, images, and planning documents. These data can be stolen from email systems as email and text messages or through file attachments. |
Downloads to insecure devices | This data exfiltration method poses an accidental insider threat. It occurs when a malicious actor accesses sensitive corporate data on a trusted device and transfers it to an insecure one, like a camera or smartphone lacking corporate security, risking data exfiltration. |
Uploads to external devices | This type of data exfiltration typically comes from malicious insiders. The inside attacker can exfiltrate data by downloading information from a secure device and then uploading it onto an external device. This external device could be a laptop, smartphone, tablet, or thumb drive. |
Human errors and non-secured behavior in the cloud | In this case, insecure cloud access poses data exfiltration risks, allowing malicious actors to manipulate virtual machines, deploy malware, and send malicious requests. Human errors and procedural issues compound the risk, potentially compromising protection measures. |
Topic | Added Value |
---|---|
Comprehensive visualization and understanding | The BPMN provides a standardized method for visualizing and understanding information flow and actions within complex processes. These standardized response procedures ensure consistency and best practices, which are crucial for effective threat mitigation. When applied to hybrid threats, this visualization allows stakeholders to see the entire threat detection, analysis, and response process. This holistic view helps identify potential vulnerabilities and bottlenecks that could be exploited in a hybrid attack. |
Enhanced coordination and communication | Clear, standardized diagrams facilitate cohesive efforts across different teams and stakeholders in threat responses, enhancing coordination and communication. By having a common visual language, everyone from IT security teams to management can understand the processes and their roles, leading to better communication and coordinated response efforts. |
Scenario simulation and analysis | Implementing standardized response procedures across different parts of an organization or across multiple organizations improves efficiency and adaptability by integrating with existing systems. This enables automated response actions based on predefined rules and events, leading to quicker responses to hybrid threats. Additionally, it allows for the simulation of various threat scenarios to analyze potential impacts and refine response plans. Testing “what-if” scenarios provides valuable insights into the resilience of the Infosec framework, enhancing preparedness for real-world incidents. |
Risk management and documentation | The BPMN provides detailed, structured documentation of threat response processes, which is crucial for regulatory compliance and audits. It shows that the organization has well-defined procedures, aiding in post-incident analyses and improving processes through lessons learned. Additionally, the BPMN helps identify critical points for implementing or enhancing security controls. This proactive risk management approach addresses potential vulnerabilities before exploitation, creating tools for prioritizing risks based on their impact on business processes. |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Pestana, G.; Sofou, S. Data Governance to Counter Hybrid Threats against Critical Infrastructures. Smart Cities 2024, 7, 1857-1877. https://doi.org/10.3390/smartcities7040072
Pestana G, Sofou S. Data Governance to Counter Hybrid Threats against Critical Infrastructures. Smart Cities. 2024; 7(4):1857-1877. https://doi.org/10.3390/smartcities7040072
Chicago/Turabian StylePestana, Gabriel, and Souzanna Sofou. 2024. "Data Governance to Counter Hybrid Threats against Critical Infrastructures" Smart Cities 7, no. 4: 1857-1877. https://doi.org/10.3390/smartcities7040072
APA StylePestana, G., & Sofou, S. (2024). Data Governance to Counter Hybrid Threats against Critical Infrastructures. Smart Cities, 7(4), 1857-1877. https://doi.org/10.3390/smartcities7040072