A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Self-Aware Cybersecurity Architecture for Autonomous Vehicles: Security through System-Level Accountability
Tekijät: Au-Kyere Akwasi, Nigussie Ethiopia, Isoaho Jouni
Kustantaja: MDPI
Kustannuspaikka: Basel
Julkaisuvuosi: 2023
Lehti: Sensors
Artikkelin numero: 8817
Vuosikerta: 23
Numero: 21
eISSN: 1424-8220
DOI: https://doi.org/10.3390/s23218817
Julkaisun avoimuus kirjaamishetkellä: Avoimesti saatavilla
Julkaisukanavan avoimuus : Kokonaan avoin julkaisukanava
Verkko-osoite: https://doi.org/10.3390/s23218817
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/182187961
Rinnakkaistallenteen lisenssi: CC BY
Rinnakkaistallennetun julkaisun versio: Kustantajan versio
The inherent dynamism of recent technological advancements in intelligent vehicles has seen multitudes of noteworthy security concerns regarding interactions and data. As future mobility embraces the concept of vehicles-to-everything, it exacerbates security complexities and challenges concerning dynamism, adaptiveness, and self-awareness. It calls for a transition from security measures relying on static approaches and implementations. Therefore, to address this transition, this work proposes a hierarchical self-aware security architecture that effectively establishes accountability at the system level and further illustrates why such a proposed security architecture is relevant to intelligent vehicles. The article provides (1) a comprehensive understanding of the self-aware security concept, with emphasis on its hierarchical security architecture that enables system-level accountability, and (2) a deep dive into each layer supported by algorithms and a security-specific in-vehicle black box with external virtual security operation center (VSOC) interactions. In contrast to the present in-vehicle security measures, this architecture introduces characteristics and properties that enact self-awareness through system-level accountability. It implements hierarchical layers that enable real-time monitoring, analysis, decision-making, and in-vehicle and remote site integration regarding security-related decisions and activities.
Ladattava julkaisu This is an electronic reprint of the original article. |