| 1. |
- Bellini, Emanuele, et al.
(author)
-
Resilience learning through self adaptation in digital twins of human-cyber-physical systems
- 2021
-
In: Proceedings of the 2021 IEEE International Conference on Cyber Security and Resilience (CSR). - : IEEE. - 9781665402859 - 9781665402866 ; , s. 168-173
-
Conference paper (peer-reviewed)abstract
- Human-Cyber-Physical-Systems (HPCS), such as critical infrastructures in modern society, are subject to several systemic threats due to their complex interconnections and interdependencies. Management of systemic threats requires a paradigm shift from static risk assessment to holistic resilience modeling and evaluation using intelligent, data-driven and run-time approaches. In fact, the complexity and criticality of HCPS requires timely decisions considering many parameters and implications, which in turn require the adoption of advanced monitoring frameworks and evaluation tools. In order to tackle such challenge, we introduce those new paradigms in a framework named RESILTRON, envisioning Digital Twins (DT) to support decision making and improve resilience in HCPS under systemic stress. In order to represent possibly complex and heterogeneous HCPS, together with their environment and stressors, we leverage on multi-simulation approaches, combining multiple formalisms, data-driven approaches and Artificial Intelligence (AI) modelling paradigms, through a structured, modular and compositional framework. DT are used to provide an adaptive abstract representation of the system in terms of multi-layered spatially-embedded dynamic networks, and to apply self-adaptation to time-warped What-If analyses, in order to find the best sequence of decisions to ensure resilience under uncertainty and continuous HPCS evolution.
|
|
| 2. |
- Bernardi, Simona, et al.
(author)
-
Model-driven availability evaluation of railway control systems
- 2011
-
In: Computer Safety, Reliability, and Security. SAFECOMP 2011. - Berlin, Heidelberg : Springer. - 9783642242694 ; , s. 15-28
-
Conference paper (peer-reviewed)abstract
- Maintenance of real-world systems is a complex task involving several actors, procedures and technologies. Proper approaches are needed in order to evaluate the impact of different maintenance policies considering cost/benefit factors. To that aim, maintenance models may be used within availability, performability or safety models, the latter developed using formal languages according to the requirements of international standards. In this paper, a model-driven approach is described for the development of formal maintenance and reliability models for the availability evaluation of repairable systems. The approach facilitates the use of formal models which would be otherwise difficult to manage, and provides the basis for automated models construction. Starting from an extension to maintenance aspects of the MARTE-DAM profile for dependability analysis, an automated process based on model-to-model transformations is described. The process is applied to generate a Repairable Fault Trees model from the MARTE-DAM specification of the Radio Block Centre - a modern railway controller. © 2011 Springer-Verlag.
|
|
| 3. |
- Besinovic, Nikola, et al.
(author)
-
Artificial Intelligence in Railway Transport : Taxonomy, Regulations, and Applications
- 2022
-
In: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:9, s. 14011-14024
-
Journal article (peer-reviewed)abstract
- Artificial Intelligence (AI) is becoming pervasive in most engineering domains, and railway transport is no exception. However, due to the plethora of different new terms and meanings associated with them, there is a risk that railway practitioners, as several other categories, will get lost in those ambiguities and fuzzy boundaries, and hence fail to catch the real opportunities and potential of machine learning, artificial vision, and big data analytics, just to name a few of the most promising approaches connected to AI. The scope of this paper is to introduce the basic concepts and possible applications of AI to railway academics and practitioners. To that aim, this paper presents a structured taxonomy to guide researchers and practitioners to understand AI techniques, research fields, disciplines, and applications, both in general terms and in close connection with railway applications such as autonomous driving, maintenance, and traffic management. The important aspects of ethics and explainability of AI in railways are also introduced. The connection between AI concepts and railway subdomains has been supported by relevant research addressing existing and planned applications in order to provide some pointers to promising directions.
|
|
| 4. |
- De Donato, Lorenzo, et al.
(author)
-
Artificial intelligence in railways : current applications, challenges, and ongoing research
- 2023
-
In: Handbook on Artificial Intelligence and Transport. - : Edward Elgar Publishing. - 9781803929538 - 9781803929545 ; , s. 249-283
-
Book chapter (peer-reviewed)abstract
- This chapter presents applications, challenges, and opportunities for the integration of artificial intelligence in rail transport, based on the current results of the European project Roadmaps for AI integration in the rail sector (RAILS). Past and ongoing research directions are briefly outlined, and then the regulatory landscape is presented as well as the main barriers to overcome. Some technical aspects are addressed to provide some valuable references, and a high-level description of ongoing research work is given, spanning from innovative studies on smart maintenance, collision avoidance, delay prediction, and incident attribution analysis to visionary scenarios such as intelligent control and virtual coupling.
|
|
| 5. |
- De Donato, Lorenzo, et al.
(author)
-
Artificial intelligence in railways : Current applications, challenges, and ongoing research
- 2023
-
In: Handbook on Artificial Intelligence and Transport. - : Edward Elgar Publishing. - 9781803929545 - 9781803929538 ; , s. 249-283
-
Book chapter (peer-reviewed)abstract
- This chapter presents applications, challenges, and opportunities for the integration of artificial intelligence in rail transport, based on the current results of the European project Roadmaps for AI integration in the rail sector (RAILS). Past and ongoing research directions are briefly outlined, and then the regulatory landscape is presented as well as the main barriers to overcome. Some technical aspects are addressed to provide some valuable references, and a high-level description of ongoing research work is given, spanning from innovative studies on smart maintenance, collision avoidance, delay prediction, and incident attribution analysis to visionary scenarios such as intelligent control and virtual coupling.
|
|
| 6. |
- De Donato, Lorenzo, et al.
(author)
-
Intelligent detection of warning bells at level crossings through deep transfer learning for smarter railway maintenance
- 2023
-
In: Engineering applications of artificial intelligence. - : Elsevier Ltd. - 0952-1976 .- 1873-6769. ; 123
-
Journal article (peer-reviewed)abstract
- Level Crossings are among the most critical railway assets, concerning both the risk of accidents and their maintainability, due to intersections with promiscuous traffic and difficulties in remotely monitoring their health status. Failures can be originated from several factors, including malfunctions in the bar mechanisms and warning devices, such as light signals and bells. This paper focuses on the intelligent detection of anomalies in warning bells through non-intrusive acoustic monitoring by: (1) introducing a new concept for autonomous monitoring of level crossings; (2) generating and sharing a specific dataset collecting relevant audio signals from publicly available audio recordings; (3) implementing and evaluating a solution combining deep learning and transfer learning for warning bell detection. The results show a high accuracy in detecting anomalies and suggest viability of the approach in real-world applications, especially where network cameras with on-board microphones are installed for multi-purpose level crossing surveillance.
|
|
| 7. |
- De Donato, Lorenzo, et al.
(author)
-
Towards AI-assisted digital twins for smart railways : preliminary guideline and reference architecture
- 2023
-
In: Journal of Reliable Intelligent Environments. - : Springer Science and Business Media Deutschland GmbH. - 2199-4668 .- 2199-4676.
-
Journal article (peer-reviewed)abstract
- In the last years, there has been a growing interest in the emerging concept of digital twins (DTs) among software engineers and researchers. DTs not only represent a promising paradigm to improve product quality and optimize production processes, but they also may help enhance the predictability and resilience of cyber-physical systems operating in critical contexts. In this work, we investigate the adoption of DTs in the railway sector, focusing in particular on the role of artificial intelligence (AI) technologies as key enablers for building added-value services and applications related to smart decision-making. In this paper, in particular, we address predictive maintenance which represents one of the most promising services benefiting from the combination of DT and AI. To cope with the lack of mature DT development methodologies and standardized frameworks, we detail a workflow for DT design and development specifically tailored to a predictive maintenance scenario and propose a high-level architecture for AI-enabled DTs supporting such workflow.
|
|
| 8. |
|
|
| 9. |
- Dirnfeld, Ruth, et al.
(author)
-
Integrating AI and DTs : challenges and opportunities in railway maintenance application and beyond
- 2024
-
In: Simulation (San Diego, Calif.). - : Sage Publications. - 0037-5497 .- 1741-3133.
-
Journal article (peer-reviewed)abstract
- In the last years, there has been a growing interest in the emerging concept of digital twin (DT) as it represents a promising paradigm to continuously monitor cyber-physical systems, as well as to test and validate predictability, safety, and reliability aspects. At the same time, artificial intelligence (AI) is exponentially affirming as an extremely powerful tool when it comes to modeling the behavior of physical assets allowing, de facto, the possibility of making predictions on their potential evolution. However, despite the fact that DTs and AI (and their combination) can act as game-changing technologies in different domains (including the railways), several challenges have to be faced to ensure their effectiveness, especially when dealing with safety-critical systems. This paper provides a narrative review of the scientific literature on DTs for railway maintenance applications, with a special focus on their relationship with AI. The aim is to discuss the opportunities the integration of these two technologies could open in railway maintenance applications (and beyond), while highlighting the main challenges that should be overcome for its effective implementation.
|
|
| 10. |
- Dirnfeld, Ruth, et al.
(author)
-
Low-Power Wide-Area Networks in Intelligent Transportation : Review and Opportunities for Smart-Railways
- 2020
-
In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020. - : IEEE. - 9781728141497 - 9781728141503 ; , s. 1-7
-
Conference paper (peer-reviewed)abstract
- Technology development in the field of the Internet of Things (IoT) and more specifically in Low-Power Wide-Area Networks (LPWANs) has enabled a whole set of new applications in several fields of Intelligent Transportation Systems. Among all, smart-railways represents one of the most challenging scenarios, due to its wide geographical distribution and strict energy-awareness. This paper aims to provide an overview of the state-of-the-art in LPWAN, with a focus on intelligent transportation. This study is part of the RAILS (Roadmaps for Artificial Intelligence integration in the raiL Sector) research project, funded by the European Union under the Shift2Rail Joint Undertaking. As a first step to meet its objectives, RAILS surveys the current state of development of technology enablers for smart-railways considering possible technology transfer from other sectors. To that aim, IoT and LPWAN technologies appear as very promising for cost-effective remote surveillance, monitoring and control over large geographical areas, by collecting data for several sensing applications (e.g., predictive condition-based maintenance, security early warning and situation awareness, etc.) even in situations where power supply is limited (e.g., where solar panels are employed) or absent (e.g., installation on-board freight cars). © 2020 IEEE.
|
|
| 11. |
- Donato, Lorenzo De, et al.
(author)
-
A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance
- 2022
-
In: IEEE Access. - : IEEE. - 2169-3536. ; 10, s. 65376-65400
-
Journal article (peer-reviewed)abstract
- Within Artificial Intelligence, Deep Learning (DL) represents a paradigm that has been showing unprecedented performance in image and audio processing by supporting or even replacing humans in defect and anomaly detection. The railway sector is expected to benefit from DL applications, especially in predictive maintenance applications, where smart audio and video sensors can be leveraged yet kept distinct from safety-critical functions. Such separation is crucial, as it allows for improving system dependability with no impact on its safety certification. This is further supported by the development of DL in other transportation domains, such as automotive and avionics, opening for knowledge transfer opportunities and highlighting the potential of such a paradigm in railways. In order to summarize the recent state-of-the-art while inquiring about future opportunities, this paper reviews DL approaches for the analysis of data generated by acoustic and visual sensors in railway maintenance applications that have been published until August 31st, 2021. In this paper, the current state of the research is investigated and evaluated using a structured and systematic method, in order to highlight promising approaches and successful applications, as well as to identify available datasets, current limitations, open issues, challenges, and recommendations about future research directions.
|
|
| 12. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
A multiformalism modular approach to ertms/etcs failure modeling
- 2014
-
In: International Journal of Reliability, Quality and Safety Engineering (IJRQSE). - : World Scientific. - 0218-5393. ; 21:1
-
Journal article (peer-reviewed)abstract
- European Railway Traffic Management System/European Train Control System (ERTMS/ETCS) is a recent standard aimed at improving performance, safety and inter-operability of modern railways. In order to be compliant to ERTMS/ETCS, a railway signalling system must meet strict nonfunctional requirements on system level failure modes. In this paper, a multiformalism model is employed to perform an availability analysis of an ERTMS/ETCS reference architecture at early phases of its development cycle. At this aim, a bottom-up analysis is performed from subsystem failure models (expressed by means of Generalized Stochastic Petri Nets, Fault Trees and Repairable Fault Trees) up to the overall system model. The modular approach, here used, allows to evaluate the influence of basic design parameters on the probability of system-level failure modes and demonstrates that system availability is within the bound required by the ERTMS/ETCS specification. The results show that the multiformalism modeling approach helps to cope with complexity, eases the verification of availability requirements and can be successfully applied to the analysis of complex critical systems. © 2014 World Scientific Publishing Company.
|
|
| 13. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
A new modeling approach to the safety evaluation of N-modular redundant computer systems in presence of imperfect maintenance
- 2009
-
In: Reliability Engineering & System Safety. - : Elsevier BV. - 0951-8320 .- 1879-0836. ; 94:9, s. 1422-1432
-
Journal article (peer-reviewed)abstract
- A large number of safety-critical control systems are based on N-modular redundant architectures, using majority voters on the outputs of independent computation units. In order to assess the compliance of these architectures with international safety standards, the frequency of hazardous failures must be analyzed by developing and solving proper formal models. Furthermore, the impact of maintenance faults has to be considered, since imperfect maintenance may degrade the safety integrity level of the system. In this paper, we present both a failure model for voting architectures based on Bayesian networks and a maintenance model based on continuous time Markov chains, and we propose to combine them according to a compositional multiformalism modeling approach in order to analyze the impact of imperfect maintenance on the system safety. We also show how the proposed approach promotes the reuse and the interchange of models as well the interchange of solving tools. © 2009 Elsevier Ltd. All rights reserved.
|
|
| 14. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
A Petri Net pattern-oriented approach for the design of physical protection systems
- 2014
-
In: Computer Safety, Reliability, and Security. SAFECOMP 2014. - Cham : Springer. - 9783319105055 ; , s. 230-245
-
Conference paper (peer-reviewed)abstract
- The design of complex Physical Protection Systems (PPSs) still raises some challenges despite the high number of technologies for smart surveillance. One reason is the lack of effective methodologies able to support the PPS designer in evaluating the effectiveness of the system on varying design choices. Indeed, an estimation of the system vulnerability should be performed in the early phases of the PPS design. This paper introduces a model-based methodology for the quantitative estimation of the vulnerability of a PPS. The proposed methodology clearly defines a compositional approach which takes advantage from the usage of predefined patterns for the creation of vulnerability models. In particular, the paper proposes some Petri Net patterns able to capture the behavioural aspects of several assets and actors involved in attacking/defending scenarios. © 2014 Springer International Publishing.
|
|
| 15. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Compositional modeling of railway Virtual Coupling with Stochastic Activity Networks
- 2021
-
In: Formal Aspects of Computing. - : Springer. - 0934-5043 .- 1433-299X. ; 33, s. 989-1007
-
Journal article (peer-reviewed)abstract
- The current travel demand in railways requires the adoption of novel approaches and technologies in order to increase network capacity. Virtual Coupling is considered one of the most innovative solutions to increase railway capacity by drastically reducing train headway. The aim of this paper is to provide an approach to investigate the potential of Virtual Coupling in railways by composing stochastic activity networks model templates. The paper starts describing the Virtual Coupling paradigm with a focus on standard European railway traffic controllers. Based on stochastic activity network model templates, we provide an approach to perform quantitative evaluation of capacity increase in reference Virtual Coupling scenarios. The approach can be used to estimate system capacity over a modelled track portion, accounting for the scheduled service as well as possible failures. Due to its modularity, the approach can be extended towards the inclusion of safety model components. The contribution of this paper is a preliminary result of the PERFORMINGRAIL (PERformance-based Formal modelling and Optimal tRaffic Management for movING-block RAILway signalling) project funded by the European Shift2Rail Joint Undertaking.
|
|
| 16. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Fuzzy decision fusion and multiformalism modelling in physical security monitoring
- 2016
-
In: Recent Advances in Computational Intelligence in Defense and Security. - Cham : Springer. - 9783319264486 - 9783319264509 ; , s. 71-100
-
Book chapter (peer-reviewed)abstract
- Modern smart-surveillance applications are based on an increasingly large number of heterogeneous sensors that greatly differ in size, cost and reliability. System complexity poses issues in its design, operation and maintenance since a large number of events needs to be managed by a limited number of operators. However, it is rather intuitive that redundancy and diversity of sensors may be advantageously leveraged to improve threat recognition and situation awareness. That can be achieved by adopting appropriate model-based decision-fusion approaches on sensor-generated events. In such a context, the challenges to be addressed are the optimal correlation of sensor events, taking into account all the sources of uncertainty, and how to measure situation recognition trustworthiness. The aim of this chapter is twofold: it deals with uncertainty by enriching existing model-based event recognition approaches with imperfect threat modelling and with the use of different formalisms improving detection performance. To that aim, fuzzy operators are defined using the probabilistic formalisms of Bayesian Networks and Generalized Stochastic Petri Nets. The main original contributions span from support physical security system design choices to the demonstration of a multiformalism approach for event correlation. The applicability of the approach is demonstrated on the case-study of a railway physical protection system.
|
|
| 17. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Model-driven V&V processes for computer based control systems : A unifying perspective
- 2012
-
In: Leveraging Applications of Formal Methods, Verification and Validation. Applications and Case Studies. ISoLA 2012. - Berlin, Heidelberg : Springer. - 9783642340314 ; , s. 190-204
-
Conference paper (peer-reviewed)abstract
- A recent trend in software engineering is to support the development process by providing flexible tool chains allowing for effective Model-Driven approaches. These solutions are very appealing in industrial settings since they enable the creation of development and verification processes, enhancing abstraction and reuse, and hence improving productivity. This paper addresses advantages and challenges in extending Model-Driven approaches to system engineering and specifically to verification and validation (V&V) of critical computer-based systems. Specifically, the paper highlights the needs for real-world industrial contexts and proposes the definition of a unifying Model-Driven process for V&V of functional and non-functional system properties. Some enabling techniques which aim at improving the reuse of Model-Driven artifacts are addressed to deal with process scalability and effectiveness. Two sample applications are described for ERTMS/ETCS signalling system in order to show the advantages of the approach: formal modeling for performance evaluation of message delivery between train and track controllers and test case generation for the verification of functional requirements of trains outdistancing. © 2012 Springer-Verlag.
|
|
| 18. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Petri net modelling of physical vulnerability
- 2013
-
In: Critical Information Infrastructure Security. CRITIS 2011. - Berlin, Heidelberg : Springer. - 9783642414756 ; , s. 128-139
-
Conference paper (peer-reviewed)abstract
- Several multi-disciplinary aspects need to be addressed in security risk evaluation, including the estimation of risk attributes. One of the most widespread definitions of security risk relates it to the attributes of: probability of occurrence (or rather "frequency") of threats, system vulnerability with respect to the threat (or rather "probability of success of the threat"), and expected consequences (or rather "damage"). In this paper we provide a straightforward generic model based on Stochastic Petri Nets which can be adopted for the quantitative evaluation of physical vulnerability. The model allows to evaluate besides effectiveness parameters (e.g. probability of sensing, assessment, neutralization, etc.) also efficiency related ones (e.g. time to sense, assess, neutralize, etc.). Some examples will be provided in order to show how the model can be used in real-world protection systems applications. © 2013 Springer-Verlag.
|
|
| 19. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Safety integrity through self-adaptation for multi-sensor event detection : Methodology and case-study
- 2020
-
In: Future generations computer systems. - : Elsevier. - 0167-739X .- 1872-7115. ; 112, s. 965-981
-
Journal article (peer-reviewed)abstract
- Traditional safety-critical systems are engineered in a way to be predictable in all operating conditions. They are common in industrial automation and transport applications where uncertainties (e.g., fault occurrence rates) can be modeled and precisely evaluated. Furthermore, they use high-cost hardware components to increase system reliability. On the contrary, future systems are increasingly required to be "smart"(or "intelligent") that is to adapt to new scenarios, learn and react to unknown situations, possibly using low-cost hardware components. In order to move a step forward to fulfilling those new expectations, in this paper we address run-time stochastic evaluation of quantitative safety targets, like hazard rate, in self-adaptive event detection systems by using Bayesian Networks and their extensions. Self-adaptation allows changing correlation schemes on diverse detectors based on their reputation, which is continuously updated to account for performance degradation as well as modifications in environmental conditions. To that aim, we introduce a specific methodology and show its application to a case-study of vehicle detection with multiple sensors for which a real-world data-set is available from a previous study. Besides providing a proof-of-concept of our approach, the results of this paper pave the way to the introduction of new paradigms in the dynamic safety assessment of smart systems. (c) 2020 Elsevier B.V. All rights reserved.
|
|
| 20. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Towards Railway Virtual Coupling
- 2018
-
In: 2018 IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC). - : IEEE. - 9781538641927
-
Conference paper (peer-reviewed)
|
|
| 21. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Towards Trustworthy Autonomous Systems : Taxonomies and Future Perspectives
- 2024
-
In: IEEE Transactions on Emerging Topics in Computing. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2168-6750. ; 12:2, s. 601-614
-
Journal article (peer-reviewed)abstract
- The class of Trustworthy Autonomous Systems (TAS) includes cyber-physical systems leveraging on self-x technologies that make them capable to learn, adapt to changes, and reason under uncertainties in possibly critical applications and evolving environments. In the last decade, there has been a growing interest in enabling artificial intelligence technologies, such as advanced machine learning, new threats, such as adversarial attacks, and certification challenges, due to the lack of sufficient explainability. However, in order to be trustworthy, those systems also need to be dependable, secure, and resilient according to well-established taxonomies, methodologies, and tools. Therefore, several aspects need to be addressed for TAS, ranging from proper taxonomic classification to the identification of research opportunities and challenges. Given such a context, in this paper address relevant taxonomies and research perspectives in the field of TAS. We start from basic definitions and move towards future perspectives, regulations, and emerging technologies supporting development and operation of TAS.
|
|
| 22. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Trustworthiness evaluation of multi-sensor situation recognition in transit surveillance scenarios
- 2013
-
In: Security Engineering and Intelligence Informatics. CD-ARES 2013. - Berlin, Heidelberg : Springer. - 9783642405877 ; , s. 442-456
-
Conference paper (peer-reviewed)abstract
- Physical Security Information Management (PSIM) systems are a recent introduction in the surveillance of critical infrastructures, like those used for mass-transit. In those systems, different sensors are integrated as separate event detection devices, each of them generating independent alarms. In order to lower the rate of false alarms and provide greater situation awareness for surveillance operators, we have developed a framework-namely DETECT-for correlating information coming from multiple heterogeneous sensors. DETECT uses detection models based on (extended) Event Trees in order to generate higher level warnings when a known threat scenario is being detected. In this paper we extend DETECT by adopting probabilistic models for the evaluation of threat detection trustworthiness on reference scenarios. The approach also allows for a quantitative evaluation of model sensitivity to sensor faults. The results of a case-study in the transit system domain demonstrate the increase of trust one could expect when using scenarios characterized in a probabilistic way for the threat detection instead of single-sensor alarms. Furthermore, we show how a model analysis can serve at design time to support decisions about the type and redundancy of detectors. © IFIP International Federation for Information Processing 2013.
|
|
| 23. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Using Bayesian Networks to evaluate the trustworthiness of '2 out of 3' decision fusion mechanisms in multi-sensor applications
- 2015
-
In: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; , s. 682-687
-
Conference paper (peer-reviewed)abstract
- The use of smart-sensors to recognize automatically complex situations (anomalous behaviors, physical security threats, etc.) requires 'intelligent' methods to improve the trustworthiness of automatic decisions. Voting and consensus mechanisms can be employed whether supported by probabilistic formalisms to correlate event occurrence, to merge local events and to estimate the likelihood of overall decisions. This paper presents the results of a quantitative comparison of three different voting schemes based on Bayesian Networks. These models present a growing complexity and they are able to provide a trustworthiness estimation based on single nodes detection reliability in terms of false alarm probabilities. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
|
|
| 24. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
-
Using repairable fault trees for the evaluation of design choices for critical repairable systems
- 2005
-
In: Proceedings of IEEE International Symposium on High Assurance Systems Engineering. - : IEEE. - 0769523773 - 9780769523774 ; , s. 163-172
-
Conference paper (peer-reviewed)abstract
- Critical repairable systems are characterized by complex architecture and requirements. The evaluation of benefits produced by repair policies on the overall system availability is not straightforward, as policies can be very articulated and different. In order to support this evaluation process, the Repairable Fault Tree (RFT) formalism revealed to be useful and suitable to represent complex repair policies by extending the existing Fault Tree formalism. In this paper we show how to exploit RFT advantages by evaluating the effects of different repair policies on the availability of the most critical component of ERTMS/ETCS (an European railway standard) systems: the Radio Block Centre (RBC).
|
|
| 25. |
- Marrone, Stefano, et al.
(author)
-
On synergies of cyber and physical security modelling in vulnerability assessment of railway systems
- 2015
-
In: Computers & electrical engineering. - : Elsevier. - 0045-7906 .- 1879-0755. ; 47, s. 275-285
-
Journal article (peer-reviewed)abstract
- The multifaceted nature of cyber-physical systems needs holistic study methods to detect essential aspects and interrelations among physical and cyber components. Like the systems themselves, security threats feature both cyber and physical elements. Although to apply divide et impera approaches helps handling system complexity, to consider just one aspect at a time does not provide adequate risk awareness and hence does not allow to design the most appropriate countermeasures. To support this claim, in this paper we provide a joint application of two model-driven techniques for physical and cyber-security evaluation. We apply two UML profiles, namely SecAM (for cyber-security) and CIP-VAM (for physical security), in combination. In such a way, we demonstrate the synergy between both profiles and the need for their tighter integration in the context of a reference case study from the railway domain. Graphical abstract © 2015 Elsevier Ltd.
|
|
| 26. |
- Marrone, Stefano, et al.
(author)
-
Towards Model-Driven V&V assessment of railway control systems
- 2014
-
In: International Journal on Software Tools for Technology Transfer. - : Springer. - 1433-2779 .- 1433-2787. ; 16:6, s. 669-683
-
Journal article (peer-reviewed)abstract
- Verification and Validation (V&V) activities aiming at certifying railway controllers are among the most critical and time-consuming in system development life cycle. As such, they would greatly benefit from novel approaches enabling both automation and traceability for assessment purposes. While several formal and Model-Based approaches have been proposed in the scientific literature, some of which are successfully employed in industrial settings, we are still far from an integrated and unified methodology which allows guiding design choices, minimizing the chances of failures/non-compliances, and considerably reducing the overall assessment effort. To address these issues, this paper describes a Model-Driven Engineering approach which is very promising to tackle the aforementioned challenges. In fact, the usage of appropriate Unified Modeling Language profiles featuring system analysis and test case specification capabilities, together with tool chains for model transformations and analysis, seems a viable way to allow end-users to concentrate on high-level holistic models and specification of non-functional requirements (i.e., dependability) and support the automation of the V&V process. We show, through a case study belonging to the railway signalling domain, how the approach is effective in supporting activities like system testing and availability evaluation. © 2014, Springer-Verlag Berlin Heidelberg.
|
|
