Cyber-Physical Systems (CPS) are composed by multiple subsystems that encompass numerous interdependencies. Although indispensable and highly performant from a functional perspective, complex interconnectivity constitutes paradoxically a significant vulnerability when an anomaly occurs. Anomalies could propagate and impact the entire CPS with irreversible consequences. This paper presents an approach to assess the anomaly propagation impact risk on a three layers oriented graph which represents the physical, digital, and system variables of a CPS components and interdependencies. Anomalies are detected applying information quality measures, while potential propagation paths are assessed computing the cumulated risk represented by weights assigned to the graph edges. To verify the cascading impact of different anomalies four cyber-attacks -denial of service, sensor offset alteration, false data injection, and replay attack -were implemented on a simulated naval water distribution CPS. The propagation impact of three anomalies was successfully assessed and the corresponding estimated propagation path, if applicable, confirmed.
To ensure a ship's fully operational status in a wide spectrum of missions, as passenger transportation, international trade, and military activities, numerous interdependent systems are essential. Despite the potential critical consequences of misunderstanding or ignoring those interdependencies, there are very few documented approaches to enable their identification, representation, analysis, and use. From the cybersecurity point of view, if an anomaly occurs on one of the interdependent systems, it could eventually impact the whole ship, jeopardizing its mission success. This paper presents a proposal to identify the main dependencies of layers within and between generic ship's functional blocks. An analysis of one of these layers, the platform systems, is developed to examine a naval cyber-physical system (CPS), the water management for passenger use, and its associated dependencies, from an intrinsic perspective. This analysis generates a three layers graph, on which dependencies are represented as oriented edges. Each abstraction level of the graph represents the physical, digital, and system variables of the examined CPS. The obtained result confirms the interest of graphs for dependencies representation and analysis. It is an operational depiction of the different systems interdependencies, on which can rely a cybersecurity evaluation, like anomaly detection and propagation assessment.
Cruise operators offer a big amount on services in high quality onboard amenities. Cruise vessels has became a target for pirates because its potential value. These attackers use more and more sophisticated tools and strategies to perform successful attacks. In consequence, detection systems need to evolve to take in account these new threats. No system are able to cover all detection requirements, so proposed solution will operate with complementary sub-systems as AIS, radar and cameras.The aim of this position paper is to introduce current threats and challenges specifically related to Automatic Identification System (AIS) anti-piracy measures and how it can be useful in fusion detection methods. We also introduce ISOLA system as a complete detection and decision aid support against, among other threats, piracy attacks.
Naval vessels infrastructures are evolving towards increasingly connected and automatic systems. Such accelerated complexity boost to search for more adapted and useful navigation devices may be at odds with cybersecurity, making necessary to develop adapted analysis solutions for experts. This paper introduces a novel process to visualize and analyze naval Cyber-Physical Systems (CPS) using oriented graphs, considering operational constraints, to represent physical and functional connections between multiple components of CPS. Rapid prototyping of interconnected components is implemented in a semi-automatic manner by defining the CPS's digital and physical systems as nodes, along with system variables as edges, to form three layers of an oriented graph, using the open-source Neo4j software suit. The generated multi-layer graph can be used to support cybersecurity analysis, like attacks simulation, anomaly detection and propagation estimation, applying existing or new algorithms.
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