Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Implicit Sensor-based Authentication of Smartphone Users with Smartwatch

Smartphones are now frequently used by end-users as the portals to cloud-based services, and smartphones are easily stolen or co-opted by an attacker. Beyond the initial log-in mechanism, it is highly desirable to re-authenticate end-users who are continuing to access security-critical services and data, whether in the cloud or in the smartphone. But attackers who have gained access to a logged-in smartphone have no incentive to re-authenticate, so this must be done in an automatic, non-bypassable way. Hence, this paper proposes a novel authentication system, iAuth, for implicit, continuous authentication of the end-user based on his or her behavioral characteristics, by leveraging the sensors already ubiquitously built into smartphones. We design a system that gives accurate authentication using machine learning and sensor data from multiple mobile devices. Our system can achieve 92.1% authentication accuracy with negligible system overhead and less than 2% battery consumption.Comment: Published in Hardware and Architectural Support for Security and Privacy (HASP), 201

Attack-Surface Metrics, OSSTMM and Common Criteria Based Approach to “Composable Security” in Complex Systems

In recent studies on Complex Systems and Systems-of-Systems theory, a huge effort has been put to cope with behavioral problems, i.e. the possibility of controlling a desired overall or end-to-end behavior by acting on the individual elements that constitute the system itself. This problem is particularly important in the “SMART” environments, where the huge number of devices, their significant computational capabilities as well as their tight interconnection produce a complex architecture for which it is difficult to predict (and control) a desired behavior; furthermore, if the scenario is allowed to dynamically evolve through the modification of both topology and subsystems composition, then the control problem becomes a real challenge. In this perspective, the purpose of this paper is to cope with a specific class of control problems in complex systems, the “composability of security functionalities”, recently introduced by the European Funded research through the pSHIELD and nSHIELD projects (ARTEMIS-JU programme). In a nutshell, the objective of this research is to define a control framework that, given a target security level for a specific application scenario, is able to i) discover the system elements, ii) quantify the security level of each element as well as its contribution to the security of the overall system, and iii) compute the control action to be applied on such elements to reach the security target. The main innovations proposed by the authors are: i) the definition of a comprehensive methodology to quantify the security of a generic system independently from the technology and the environment and ii) the integration of the derived metrics into a closed-loop scheme that allows real-time control of the system. The solution described in this work moves from the proof-of-concepts performed in the early phase of the pSHIELD research and enrich es it through an innovative metric with a sound foundation, able to potentially cope with any kind of pplication scenarios (railways, automotive, manufacturing, ...)

Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways

[Abstract] Nowadays, the railway industry is in a position where it is able to exploit the opportunities created by the IIoT (Industrial Internet of Things) and enabling communication technologies under the paradigm of Internet of Trains. This review details the evolution of communication technologies since the deployment of GSM-R, describing the main alternatives and how railway requirements, specifications and recommendations have evolved over time. The advantages of the latest generation of broadband communication systems (e.g., LTE, 5G, IEEE 802.11ad) and the emergence of Wireless Sensor Networks (WSNs) for the railway environment are also explained together with the strategic roadmap to ensure a smooth migration from GSM-R. Furthermore, this survey focuses on providing a holistic approach, identifying scenarios and architectures where railways could leverage better commercial IIoT capabilities. After reviewing the main industrial developments, short and medium-term IIoT-enabled services for smart railways are evaluated. Then, it is analyzed the latest research on predictive maintenance, smart infrastructure, advanced monitoring of assets, video surveillance systems, railway operations, Passenger and Freight Information Systems (PIS/FIS), train control systems, safety assurance, signaling systems, cyber security and energy efficiency. Overall, it can be stated that the aim of this article is to provide a detailed examination of the state-of-the-art of different technologies and services that will revolutionize the railway industry and will allow for confronting today challenges.Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431C 2016-045Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED341D R2016/012Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431G/01Agencia Estatal de Investigación (España); TEC2013-47141-C4-1-RAgencia Estatal de Investigación (España); TEC2015-69648-REDCAgencia Estatal de Investigación (España); TEC2016-75067-C4-1-

Personalized Ambience: An Integration of Learning Model and Intelligent Lighting Control

The number of households and offices adopting automation system is on the rise. Although devices and actuators can be controlled through wireless transmission, they are mostly static with preset schedules, or at different times it requires human intervention. This paper presents a smart ambience system that analyzes the user’s lighting habits, taking into account different environmental context variables and user needs in order to automatically learn about the user’s preferences and automate the room ambience dynamically. Context information is obtained from Yahoo Weather and environmental data pertaining to the room is collected via Cubesensors to study the user’s lighting habits. We employs a learning model known as the Reduced Error Prune Tree (REPTree) to analyze the users’ preferences, and subsequently predicts the preferred lighting condition to be actuated in real time through Philips Hue. The system is able to ensure the user’s comfort at all time by performing a closed feedback control loop which checks and maintains a suitable lighting ambience at optimal level

An SDN-based architecture for security provisioning in Fog-to-Cloud (F2C) computing systems

The unstoppable adoption of cloud and fog computing is paving the way to developing innovative services, some requiring features not yet covered by either fog or cloud computing. Simultaneously, nowadays technology evolution is easing the monitoring of any kind of infrastructure, be it large or small, private or public, static or dynamic. The fog-to-cloud computing (F2C) paradigm recently came up to support foreseen and unforeseen services demands while simultaneously benefiting from the smart capacities of the edge devices. Inherited from cloud and fog computing, a challenging aspect in F2C is security provisioning. Unfortunately, security strategies employed by cloud computing require computation power not supported by devices at the edge of the network, whereas security strategies in fog are yet on their infancy. Put this way, in this paper we propose Software Defined Network (SDN)-based security management architecture based on a master/slave strategy. The proposed architecture is conceptually applied to a critical infrastructure (CI) scenario, thus analyzing the benefits F2C may bring for security provisioning in CIs.Peer ReviewedPostprint (published version