In today’s data-driven world, the interconnection and automation of daily processes have become essential. As the demand for Internet connectivity grows, so does the need for robust cybersecurity measures. Operational Technology (OT), pivotal in controlling critical infrastructures such as power plants and water distribution systems, remains highly vulnerable. Many OT systems still rely on "air gaps" for security, a measure increasingly insufficient as more systems connect to the internet for remote operation and data analysis. This article addresses the critical need for enhanced OT security solutions by introducing a novel tool focused on intelligent systems for the effective detection of cyber-attacks. The tool automates the creation of attack graphs and extracts attack paths from a JSON file describing the OT network. Leveraging the MulVAL attack graph generation engine, it provides a comprehensive visualization of potential attack vectors, enhancing the capability to identify and mitigate security threats in OT environments.
Enhancing OT Threat Modelling: An Effective Rule-Based Approach for Attack Graph Generation / Sunder, Giulio; Colletto, ALBERTO SALVATORE; Raimondi, Sara; Basile, Cataldo; Viticchie', Alessio; Aliberti, Alessandro. - ELETTRONICO. - (2024). (Intervento presentato al convegno 2024 4th Intelligent Cybersecurity Conference (ICSC) tenutosi a Valencia (SP) nel 17–20 September, 2024).
Enhancing OT Threat Modelling: An Effective Rule-Based Approach for Attack Graph Generation
Alberto Salvatore Colletto;Cataldo Basile;Alessio Viticchie';Alessandro Aliberti
2024
Abstract
In today’s data-driven world, the interconnection and automation of daily processes have become essential. As the demand for Internet connectivity grows, so does the need for robust cybersecurity measures. Operational Technology (OT), pivotal in controlling critical infrastructures such as power plants and water distribution systems, remains highly vulnerable. Many OT systems still rely on "air gaps" for security, a measure increasingly insufficient as more systems connect to the internet for remote operation and data analysis. This article addresses the critical need for enhanced OT security solutions by introducing a novel tool focused on intelligent systems for the effective detection of cyber-attacks. The tool automates the creation of attack graphs and extracts attack paths from a JSON file describing the OT network. Leveraging the MulVAL attack graph generation engine, it provides a comprehensive visualization of potential attack vectors, enhancing the capability to identify and mitigate security threats in OT environments.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2992842