SecuriDN v. 0.1 is a tool for representing IT and OT assets in Distributed Energy Resources (DERs) control networks and assessing their security risks. It uses architecture graphs, attack graphs, and Dynamic Bayesian Networks (DBNs) to model and analyze potential cyberattacks. The tool’s features and goals are demonstrated through a realistic case study.<\/p>\n","protected":false},"author":93,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"tags":[1344,1346,1434,1330],"targets":[1314,1317],"pubblicazioni_tipologie":[773],"class_list":["post-203465","pubblicazioni","type-pubblicazioni","status-publish","hentry","tag-cybersecurity-en","tag-cybersecurity-assessment-en","tag-network-security","tag-security-en","targets-press-media-en","targets-research","pubblicazioni_tipologie-isi-article-en"],"acf":{"dont_show_hompage":true,"projects":{"ID":188406,"post_author":"93","post_date":"2024-06-13 15:10:14","post_date_gmt":"2024-06-13 13:10:14","post_content":"","post_title":"Integrated Project for Energy System Cybersecurity","post_excerpt":"The project has the threefold goal of developing studies, tools and methodologies aimed at: \n- ensuring the security of communication technologies in energy systems; \n- preserving the resilience of the electricity system in case of cyber attacks; \n- leveraging artificial intelligence for the detection of cyber anomalies in energy infrastructure.\n","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"integrated-project-for-energy-system-cybersecurity","to_ping":"","pinged":"","post_modified":"2024-07-02 10:30:09","post_modified_gmt":"2024-07-02 08:30:09","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.rse-web.it\/progetti\/integrated-project-for-energy-system-cybersecurity\/","menu_order":0,"post_type":"progetti","post_mime_type":"","comment_count":"0","filter":"raw"},"order_posts":"","dont_show_search":false,"related_posts":false,"show_on_slider":false,"single_post_data":{"titolo_spot":"","post_content":"
SecuriDN v. 0.1 is a tool for the representation of the assets composing the IT and the OT subsystems of Distributed Energy Resources (DERs) control networks and the possible cyberattacks that can threaten them. It is part of a platform that allows the evaluation of the security risks of DER control systems.<\/p>\n
<\/p>\n
SecuriDN is a multi-formalism tool, meaning that it manages several types of models: architecture graph, attack graphs and Dynamic Bayesian Networks (DBNs). In particular, each asset in the architecture is characterized by an attack graph showing the combinations of attack techniques that may affect the asset.<\/p>\n
<\/p>\n
By merging the attack graphs according to the asset associations in the architecture, a DBN is generated. Then, the evidence-based and time-driven probabilistic analysis of the DBN permits the quantification of the system security level. Indeed, the DBN probabilistic graphical model can be analyzed through inference algorithms, suitable for forward and backward assessment of the system\u2019s belief state.<\/p>\n
<\/p>\n
In this paper, the features and the main goals of SecuriDN are described and illustrated through a simplified but realistic case study.<\/p>\n","scarica_file":false,"link_estreno":[{"link_text":"Download Publication","link":"https:\/\/www.mdpi.com\/1996-1073\/17\/16\/3882"}],"button":{"text":"","link":""},"referente_group":false,"data_emissione":"2024-08-06","autori":"D. Cerotti, D. Codetta Raiteri, L. Egidi, G. Franceschinis, L. Portinale (Universit\u00e0 del Piemonte Orientale), D. Savarro (Universit\u00e0 di Torino), G. Dondossola, R. Terruggia (RSE S.p.A.)","destinazione":"MDPI Energies, Vol. 17, N. 3882, 6 Agosto 2024","rif_rse":"24008902"},"satellite_post_url":""},"yoast_head":"\n