6,962 research outputs found
Design-Time Quantification of Integrity in Cyber-Physical-Systems
In a software system it is possible to quantify the amount of information
that is leaked or corrupted by analysing the flows of information present in
the source code. In a cyber-physical system, information flows are not only
present at the digital level, but also at a physical level, and to and fro the
two levels. In this work, we provide a methodology to formally analyse a
Cyber-Physical System composite model (combining physics and control) using an
information flow-theoretic approach. We use this approach to quantify the level
of vulnerability of a system with respect to attackers with different
capabilities. We illustrate our approach by means of a water distribution case
study
A Storm in an IoT Cup: The Emergence of Cyber-Physical Social Machines
The concept of social machines is increasingly being used to characterise
various socio-cognitive spaces on the Web. Social machines are human
collectives using networked digital technology which initiate real-world
processes and activities including human communication, interactions and
knowledge creation. As such, they continuously emerge and fade on the Web. The
relationship between humans and machines is made more complex by the adoption
of Internet of Things (IoT) sensors and devices. The scale, automation,
continuous sensing, and actuation capabilities of these devices add an extra
dimension to the relationship between humans and machines making it difficult
to understand their evolution at either the systemic or the conceptual level.
This article describes these new socio-technical systems, which we term
Cyber-Physical Social Machines, through different exemplars, and considers the
associated challenges of security and privacy.Comment: 14 pages, 4 figure
Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD
Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings
Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations
As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance
A Design Approach to IoT Endpoint Security for Production Machinery Monitoring
The Internet of Things (IoT) has significant potential in upgrading legacy production machinery with monitoring capabilities to unlock new capabilities and bring economic benefits. However, the introduction of IoT at the shop floor layer exposes it to additional security risks with potentially significant adverse operational impact. This article addresses such fundamental new risks at their root by introducing a novel endpoint security-by-design approach. The approach is implemented on a widely applicable production-machinery-monitoring application by introducing real-time adaptation features for IoT device security through subsystem isolation and a dedicated lightweight authentication protocol. This paper establishes a novel viewpoint for the understanding of IoT endpoint security risks and relevant mitigation strategies and opens a new space of risk-averse designs that enable IoT benefits, while shielding operational integrity in industrial environments
Towards an Organizationally-Relevant Quantification of Cyber Resilience
Given the difficulty of fully securing complex cyber systems, there is growing interest in making cyber systems resilient to the cyber threat. However, quantifying the resilience of a system in an organizationally-relevant manner remains a challenge. This paper describes initial research into a novel metric for quantifying the resilience of a system to cyber threats called the Resilience Index (RI). We calculate the RI via an effects-based discrete event stochastic simulation that runs a large number of trials over a designated mission timeline. During the trials, adverse cyber events (ACEs) occur against cyber assets in a target system. We consider a trial a failure if an ACE causes the performance of any of the target system’s mission essential functions (MEFs) to fall below its assigned threshold level. Once all trials have completed, the simulator computes the ratio of successful trials to the total number of trials, yielding RI. The linkage of ACEs to MEFs provides the organizational tie
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