Large vessels are safety-critical systems where operations, performance and component availability are continuously monitored by means of multiple sensors producing large amount of data. Relevant information is preserved in Event Data Recorders that are fundamental for the reconstruction of scenarios related to serious malfunctions and incidents in technical and legal terms. By considering the state-of-the-art and two important naval accidents we evidence some issues related to the exploitation of recorded data in reconstructing the events timeline and the semantics of the scenarios. These studies motivate our proposal that aims to guarantee strong data integrity and availability of all information registered in Event Data Recorders. Our results are fundamental for the precise identification of the sequences of events and for the correct attribution of human and/or machine responsibilities.
Digital Forensics in Vessel Transportation Systems / Cantelli-Forti, A.; Colajanni, M.. - 12056:(2020), pp. 354-362. (Intervento presentato al convegno 12th International Symposium on Foundations and Practice of Security, FPS 2019 tenutosi a fra nel 2019) [10.1007/978-3-030-45371-8_23].
Digital Forensics in Vessel Transportation Systems
Colajanni M.
2020
Abstract
Large vessels are safety-critical systems where operations, performance and component availability are continuously monitored by means of multiple sensors producing large amount of data. Relevant information is preserved in Event Data Recorders that are fundamental for the reconstruction of scenarios related to serious malfunctions and incidents in technical and legal terms. By considering the state-of-the-art and two important naval accidents we evidence some issues related to the exploitation of recorded data in reconstructing the events timeline and the semantics of the scenarios. These studies motivate our proposal that aims to guarantee strong data integrity and availability of all information registered in Event Data Recorders. Our results are fundamental for the precise identification of the sequences of events and for the correct attribution of human and/or machine responsibilities.
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