1. |
- Assenza, Giacomo, et al.
(author)
-
White Paper on Industry Experiences in Critical Information Infrastructure Security : A Special Session at CRITIS 2019
- 2020
-
In: Critical Information Infrastructures Security14th International Conference, CRITIS 2019. - Cham : Springer. - 9783030376697 - 9783030376703 ; , s. 197-207
-
Book chapter (peer-reviewed)abstract
- The security of critical infrastructures is of paramount importance nowadays due to the growing complexity of components and applications. This paper collects the contributions to the industry dissemination session within the 14th International Conference on Critical Information Infrastructures Security (CRITIS 2019). As such, it provides an overview of recent practical experience reports in the field of critical infrastructure protection (CIP), involving major industry players. The set of cases reported in this paper includes the usage of serious gaming for training infrastructure operators, integrated safety and security management in the chemical/process industry, risks related to the cyber-economy for energy suppliers, smart troubleshooting in the Internet of Things (IoT), as well as intrusion detection in power distribution Supervisory Control And Data Acquisition (SCADA). The session has been organized to stimulate an open scientific discussion about industry challenges, open issues and future opportunities in CIP research.
|
|
2. |
- 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.
|
|
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. |
- Bucaioni, Alessio, 1987-, et al.
(author)
-
Towards Model-Based Performability Evaluation of Production Systems
- 2020
-
In: Work-in-progress at IEEE International Conference on Emerging Technologies and Factory Automation WIP@ETFA. - 9781728189567 ; , s. 1085-1088
-
Conference paper (peer-reviewed)abstract
- Future smart factories will be increasingly required to predict expected performance and dependability metrics related to their production processes. Domain-specific metrics include overall equipment effectiveness that measures production system availability/uptime, performance/speed and output quality. In this work-in-progress paper, we take initial steps towards a model-based approach to evaluate production-specific metrics using domain-specific languages, model transformations and stochastic modelling formalism
|
|
5. |
- Canonico, R., et al.
(author)
-
Automatic Generation of Domain-Aware Control Plane Logic for Software Defined Railway Communication Networks
- 2022
-
In: Lecture Notes in Computer Science, vol. 13704. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783031197611 ; , s. 308-320
-
Conference paper (peer-reviewed)abstract
- The emergence of 5G technologies opens up new opportunities for railway communications. One of the foundational aspects of 5G architecture is its control-plane programmability, which can be achieved through Software Defined Networking (SDN). In railway scenarios, this can be used to dynamically reconfigure the network for a more effective and efficient management of communication flows produced by moving trains. The paper presents a framework for integrating modelling and analysis tools into a programmable control plane specifically tailored to railway communications. We introduce the concept of domain-awareness in the network control plane as an SDN-enabled feature that allows achieving application-specific advantages besides those purely expressed in terms of key performance indicators such as the quality of service. We propose a reference architecture in which domain-awareness in the control plane is obtained by considering information gathered by network devices and ad-hoc communication gateways that are able to detect relevant signalling events. In the architecture, the actual behaviour of the SDN controller is governed by applications that are able to react to specific triggers and re-configure network devices accordingly. We also provide a methodological framework based on model-driven engineering and formal methods, including dynamic state machines, for the automatic generation of SDN control plane logic.
|
|
6. |
- Caporuscio, Mauro, 1975-, et al.
(author)
-
Smart-troubleshooting connected devices : Concept, challenges and opportunities
- 2020
-
In: Future generations computer systems. - : Elsevier. - 0167-739X .- 1872-7115. ; 111, s. 681-697
-
Journal article (peer-reviewed)abstract
- Today’s digital world and evolving technology has improved the quality of our lives but it has also come with a number of new threats. In the society of smart-cities and Industry 4.0, where many cyber-physical devices connect and exchange data through the Internet of Things, the need for addressing information security and solve system failures becomes inevitable. System failures can occur because of hardware failures, software bugs or interoperability issues. In this paper we introduce the industry-originated concept of “smart-troubleshooting” that is the set of activities and tools needed to gather failure information generated by heterogeneous connected devices, analyze them, and match them with troubleshooting instructions and software fixes. As a consequence of implementing smart-troubleshooting, the system would be able to self-heal and thus become more resilient. This paper aims to survey frameworks, methodologies and tools related to this new concept, and especially the ones needed to model, analyze and recover from failures in a (semi)automatic way. Smart-troubleshooting has a relation with event analysis to perform diagnostics and prognostics on devices manufactured by different suppliers in a distributed system. It also addresses management of appropriate product information specified in possibly unstructured formats to guide the troubleshooting workflow in identifying fault–causes and solutions. Relevant research is briefly surveyed in the paper in order to highlight current state-of-the-art, open issues, challenges to be tackled and future opportunities in this emerging industry paradigm.
|
|
7. |
- D’Aniello, G., et al.
(author)
-
Situation Awareness in the Cloud-Edge Continuum
- 2024
-
In: Lecture Notes on Data Engineering and Communications Technologies. - : Springer Science and Business Media Deutschland GmbH. ; , s. 307-316
-
Book chapter (other academic/artistic)abstract
- Edge Computing is becoming a promising computing paradigm that addresses the limitations of cloud computing concerning latency, autonomy, and costs. To facilitate more intelligent applications made possible by the Edge Computing paradigm, it is essential to integrate intelligence and adaptability into devices located at the network’s edge. The paper explores the potential integration of Situation Awareness (SA) capabilities into the Cloud-Edge continuum. This integration aims to empower smarter applications while effectively managing challenges related to low latency, high autonomy, and cost-effective solutions. Within our illustrative example in healthcare, we showcase how the proposed SA cloud-edge continuum architecture enables efficient data processing and decision-making.
|
|
8. |
- De Benedictis, A., et al.
(author)
-
Digital Twins for Anomaly Detection in the Industrial Internet of Things : Conceptual Architecture and Proof-of-Concept
- 2023
-
In: IEEE Transactions on Industrial Informatics. - : IEEE Computer Society. - 1551-3203 .- 1941-0050. ; 19:12, s. 11553-11563
-
Journal article (peer-reviewed)abstract
- Modern cyber-physical systems based on the industrial Internet of Things (IIoT) can be highly distributed and heterogeneous, and that increases the risk of failures due to misbehavior of interconnected components, or other interaction anomalies. In this article, we introduce a conceptual architecture for IIoT anomaly detection based on the paradigms of digital twins (DT) and autonomic computing (AC), and we test it through a proof-of-concept of industrial relevance. The architecture is derived from the current state-of-the-art in DT research and leverages on the MAPE-K feedback loop of AC in order to monitor, analyze, plan, and execute appropriate reconfiguration or mitigation strategies based on the detected deviation from prescriptive behavior stored as shared knowledge. We demonstrate the approach and discuss results by using a reference operational scenario of adequate complexity and criticality within the European Railway Traffic Management System.
|
|
9. |
- 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.
|
|
10. |
- 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.
|
|