Jani Suomalainen , Ijaz Ahmad , Annette Shajan , Tapio Savunen
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引用次数: 0
Abstract
Edge intelligence, network autonomy, broadband satellite connectivity, and other concepts for private 6G networks are enabling new applications for public safety authorities, e.g., for police and rescue personnel. Enriched situational awareness, group communications with high-quality video, large scale IoT, and remote control of vehicles and robots will become available in any location and situation. We analyze cybersecurity in intelligent tactical bubbles, i.e., in autonomous rapidly deployable mobile networks for public safety operations. Machine learning plays major roles in enabling these networks to be rapidly orchestrated for different operations and in securing these networks from emerging threats, but also in enlarging the threat landscape. We explore applicability of different threat and risk analysis methods for mission-critical networked applications. We present the results of a joint risk prioritization study. We survey security solutions and propose a security architecture, which is founded on the current standardization activities for terrestrial and non-terrestrial 6G and leverages the concepts of machine learning-based security to protect mission-critical assets at the edge of the network.
期刊介绍:
Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications.
Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration.
Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.