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Flammini, Francesco, Senior LecturerORCID iD iconorcid.org/0000-0002-2833-7196
Publications (10 of 96) Show all publications
Assenza, G., Cozzani, V., Flammini, F., Gotcheva, N., Gustafsson, T., Hansson, A., . . . Young, H. (2020). White Paper on Industry Experiences in Critical Information Infrastructure Security: A Special Session at CRITIS 2019. In: Simin Nadjm-Tehrani (Ed.), Nadjm-Tehrani, Simin (Ed.), Critical Information Infrastructures Security14th International Conference, CRITIS 2019,: Linköping, Sweden, September 23–25, 2019, Revised Selected Papers (pp. 197-207). Springer
Open this publication in new window or tab >>White Paper on Industry Experiences in Critical Information Infrastructure Security: A Special Session at CRITIS 2019
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2020 (English)In: Critical Information Infrastructures Security14th International Conference, CRITIS 2019,: Linköping, Sweden, September 23–25, 2019, Revised Selected Papers / [ed] Simin Nadjm-Tehrani, Springer, 2020, p. 197-207Chapter in book (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer, 2020
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11777
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-90657 (URN)10.1007/978-3-030-37670-3_18 (DOI)978-3-030-37669-7 (ISBN)978-3-030-37670-3 (ISBN)
Available from: 2019-12-22 Created: 2019-12-22 Last updated: 2020-01-29Bibliographically approved
Pappaterra, M. & Flammini, F. (2019). A Review of Intelligent Cybersecurity with Bayesian Networks. In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC): . Paper presented at 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Bari, Italy, 6-9 Okt. 2019 (pp. 445-452). IEEE
Open this publication in new window or tab >>A Review of Intelligent Cybersecurity with Bayesian Networks
2019 (English)In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), IEEE, 2019, p. 445-452Conference paper, Published paper (Refereed)
Abstract [en]

Cybersecurity threats have surged in the past decades. Experts agree that conventional security measures will soon not be enough to stop the propagation of more sophisticated and harmful cyberattacks. Recently, there has been a growing interest in mastering the complexity of cybersecurity by adopting methods borrowed from Artificial Intelligence (AI) in order to support automation. In this paper, we provide a brief survey and some hints about Bayesian Network applications to intelligent cybersecurity in order to enable quantitative threat assessment for superior risk analysis and situation awareness.

Place, publisher, year, edition, pages
IEEE, 2019
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-90355 (URN)10.1109/SMC.2019.8913864 (DOI)978-1-7281-4569-3 (ISBN)978-1-7281-4570-9 (ISBN)978-1-7281-4568-6 (ISBN)
Conference
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Bari, Italy, 6-9 Okt. 2019
Available from: 2019-12-02 Created: 2019-12-02 Last updated: 2019-12-19Bibliographically approved
Tokody, D., Papp, J., Iantovics, L. B. & Flammini, F. (2019). Complex, Resilient and Smart Systems. In: Francesco Flammini (Ed.), Resilience of Cyber-Physical Systems: From Risk Modelling to Threat Counteraction (pp. 3-24). Springer
Open this publication in new window or tab >>Complex, Resilient and Smart Systems
2019 (English)In: Resilience of Cyber-Physical Systems: From Risk Modelling to Threat Counteraction / [ed] Francesco Flammini, Springer, 2019, p. 3-24Chapter in book (Refereed)
Place, publisher, year, edition, pages
Springer, 2019
Series
Advanced Sciences and Technologies for Security Applications, ISSN 1613-5113, E-ISSN 2363-9466
National Category
Computer Sciences Computer Systems
Identifiers
urn:nbn:se:lnu:diva-80582 (URN)10.1007/978-3-319-95597-1_1 (DOI)978-3-319-95596-4 (ISBN)
Available from: 2019-02-16 Created: 2019-02-16 Last updated: 2019-03-06Bibliographically approved
Saman Azari, M., Flammini, F., Caporuscio, M. & Santini, S. (2019). Data-Driven Fault Diagnosis of Once-through Benson Boilers. In: 2019 4th International Conference on System Reliability and Safety (ICSRS): . Paper presented at 2019 4th International Conference on System Reliability and Safety (ICSRS) (pp. 345-354).
Open this publication in new window or tab >>Data-Driven Fault Diagnosis of Once-through Benson Boilers
2019 (English)In: 2019 4th International Conference on System Reliability and Safety (ICSRS), 2019, p. 345-354Conference paper, Published paper (Refereed)
Abstract [en]

Fault diagnosis (FD) of once-through Benson boilers, as a crucial equipment of many thermal power plants, is of paramount importance to guarantee continuous performance. In this study, a new fault diagnosis methodology based on data-driven methods is presented to diagnose faults in once-through Benson boilers. The present study tackles this issue by adopting a combination of data-driven methods to improve the robustness of FD blocks. For this purpose, one-class versions of minimum spanning tree and K-means algorithms are employed to handle the strong interaction between measurements and part load operation and also to reduce computation time and system training error. Furthermore, an adaptive neuro-fuzzy inference system algorithm is adopted to improve accuracy and robustness of the proposed fault diagnosing system by fusion of the output of minimum spanning tree (MST) and K-means algorithms. Performance of the presented scheme against six major faults is then assessed by analyzing several test scenario.

Keywords
fault diagnosis;once-through boiler;data-driven;data fusion;MST;K-means;ANFIS
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-92153 (URN)10.1109/ICSRS48664.2019.8987699 (DOI)
Conference
2019 4th International Conference on System Reliability and Safety (ICSRS)
Available from: 2020-02-17 Created: 2020-02-17 Last updated: 2020-02-17
Meo, C. D., Vaio, M. D., Flammini, F., Nardone, R., Santini, S. & Vittorini, V. (2019). ERTMS/ETCS Virtual Coupling: Proof of Concept and Numerical Analysis. IEEE transactions on intelligent transportation systems (Print), 1-12
Open this publication in new window or tab >>ERTMS/ETCS Virtual Coupling: Proof of Concept and Numerical Analysis
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2019 (English)In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, p. 1-12Article in journal (Refereed) Epub ahead of print
Abstract [en]

Railway infrastructure operators need to push their network capacity up to their limits in high-traffic corridors. Virtual coupling is considered among the most relevant innovations to be studied within the European Horizon 2020 Shift2Rail Joint Undertaking as it can drastically reduce headways and thus increase the line capacity by allowing to dynamically connect two or more trains in a single convoy. This paper provides a proof of concept of Virtual coupling by introducing a specific operating mode within the European rail traffic management system/European train control system (ERTMS/ETCS) standard specification, and by defining a coupling control algorithm accounting for time-varying delays affecting the communication links. To that aim, we define one ploy to enrich the ERTMS/ETCS with Virtual coupling without changing its working principles and we borrow a numerical analysis methodology used to study platooning in the automotive field. The numerical analysis is also provided to support the proof of concept with quantitative results in a case-study simulation scenario.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
CPS, safety, modeling, reliability, signalling, railways, ERTMS/ETCS, automatic train control, virtual coupling, simulation, numerical analysis
National Category
Computer Systems Embedded Systems
Research subject
Computer and Information Sciences Computer Science, Computer Science; Computer and Information Sciences Computer Science; Computer Science, Software Technology; Computer and Information Sciences Computer Science, Information Systems
Identifiers
urn:nbn:se:lnu:diva-86013 (URN)10.1109/TITS.2019.2920290 (DOI)
Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2020-01-29
Flammini, F. (2019). Sistemi autonomi simbiotici e sicurezza. Mondo Digitale (80)
Open this publication in new window or tab >>Sistemi autonomi simbiotici e sicurezza
2019 (Italian)In: Mondo Digitale, ISSN 1720-898X, no 80Article in journal (Other academic) Published
Abstract [en]

This paper addresses the security of the interactions between machines and humans in the context of Symbiotic Autonomous Systems (SAS). In particular, the paper will provide an overview of the security in interconnected devices, including cybersecurity and Cyber-Physical Systems (CPS) security. We will also mention some recent security developments related to the Internet of Things (IoT).

Place, publisher, year, edition, pages
Italy: , 2019
Keywords
CPS, Autonomous Systems, Artificial Intelligence, Internet of Things, Security, Safety, Resilience
National Category
Computer Systems
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-81071 (URN)
Available from: 2019-03-14 Created: 2019-03-14 Last updated: 2019-03-21Bibliographically approved
Caporuscio, M., Flammini, F., Khakpour, N., Singh, P. & Thornadtsson, J. (2019). Smart-troubleshooting connected devices: Concept, challenges and opportunities. Future generations computer systems
Open this publication in new window or tab >>Smart-troubleshooting connected devices: Concept, challenges and opportunities
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2019 (English)In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115Article in journal (Refereed) Epub ahead of print
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
ResilienceDependabilityFault-toleranceSelf-healingSelf-repairDiagnosticsPrognosticsEvent correlationLog analyticsEmbedded systemsCyber-physical systemsInternet of Things
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-89173 (URN)10.1016/j.future.2019.09.004 (DOI)
Projects
Smart-Troubleshooting in the Connected Society (DISA SEED funding)
Available from: 2019-09-17 Created: 2019-09-17 Last updated: 2020-01-29
Broschert, S., Coughlin, T., Ferraris, M., Flammini, F., Florido, J. G., Gonzalez, A. C., . . . Yousif, M. (2019). Symbiotic Autonomous Systems: White Paper III. IEEE
Open this publication in new window or tab >>Symbiotic Autonomous Systems: White Paper III
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2019 (English)Report (Other (popular science, discussion, etc.))
Place, publisher, year, edition, pages
IEEE, 2019. p. 140
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science; Computer Science, Software Technology; Computer and Information Sciences Computer Science, Media Technology
Identifiers
urn:nbn:se:lnu:diva-90013 (URN)
Available from: 2019-11-12 Created: 2019-11-12 Last updated: 2019-12-20Bibliographically approved
Flammini, F. (2018). Artificial Intelligence (AI) applicata agli Autonomous Systems. Centro Alti Studi per la Difesa
Open this publication in new window or tab >>Artificial Intelligence (AI) applicata agli Autonomous Systems
2018 (Italian)Book (Other academic)
Alternative title[en]
Artificial Intelligence applied to Autonomous Systems
Abstract [en]

The study of artificial intelligence applied to autonomous systems has in recent years aroused growing interest at the international level, and it is expected that this interest will continue to grow in the coming years [34]. It is a fairly well known fact that in the past many technologies now used in the civil field have seen the light, more or less secretly, in the military sector. Consider, for example, the so-called ARPANET, developed by the US defense department, which anticipated the modern Internet, but also algorithms for data encryption, thermal cameras, and many other commonly used technologies. Today the scenario has partly changed, shifting the leadership of innovation towards other domains, since there is a considerable boost to the technological development in the civil field with the advance of connected society paradigms like Smart-City and Industry 4.0. One example is related to the self-driving vehicles, born in the military sector, which are developing more rapidly in the civil sphere with the attractive self-driving cars. It is therefore important to transfer enabling technologies from one domain to another (cross-fertilization) and to draw appropriately from the outside (open innovation). This is achieved through studies and researches such as the one addressed by this monograph. The objective of this study is to analyze the principles, the basic methodologies and the operational tools of artificial intelligence applied to autonomous systems, at the modeling and technology level, in order to replace human-controlled vehicles with autonomous or semi-autonomous vehicles (e.g. drones) in high-risk operating environments, as well as to reduce human errors and to speed up response times, for example in operations command and control centers. The study presents an overview of the information fusion approaches to enable artificial cognition, mentioning several relevant applications in the military field, already at an advanced phase of development or even at an embryonic level. These approaches can be used to strengthen weapon systems and defense means, with greater ability to adapt to the operational context for the dynamic management of uncertainties and unforeseen events, as well as for experiential evolution and learning. Future applications include not only self-driving vehicles and smart weapons, but also the strengthening of soldiers through prosthetics and exoskeletons. Many of the future projections have been formalized by the working group on Symbiotic Autonomous Systems – which the writer is a member of – of the Institute of Electrical and Electronics Engineers (IEEE), enclosed in a special White Paper [34]. The present study addresses the impact of the Artificial Intelligence (AI) on the use of the military instrument when this technology will be applied to military assets and weapon systems, taking into account the different declinations of AI, including: • deterministic (semi)autonomous systems implemented through Boolean logical operators (eg Event Trees); • (semi)Autonomous systems based on probabilistic / stochastic models for the representation of knowledge and inference (eg Bayesian Networks); • (semi)Autonomous systems based on trained artificial neuronal models (ANN, Artificial Neural Networks). These approaches are based on different models of machine learning, which can be supervised or not. They apply to classification and clustering approaches in modern data analysis approaches, particularly in the presence of large amounts of information (big data analytics). This study distinguishes between semi-autonomous AI models, which require the confirmation of decisions by human operators (DSS, Decision Support Systems), and complete autonomy, which presents predictability problems impacting the verification and validation process and therefore system safety. These are the cases in which the aforementioned ethical, procedural, normative and legal implications are more relevant [1]. The introduction of autonomous systems equipped with artificial intelligence involves transformations also at the level of military logistics, which can be interpreted in two directions. On the one hand, it is necessary to plan the procurement of enabling technologies, the so-called deployable systems based on secure wireless networks, and the updating of systems to support complete digitalisation, which is an essential pre-requisite for the adoption of the instrument. The other side of the coin is the use of a higher level of automation in military logistics, supported by the AI. Here we can mention the automatic multi-objective optimization algorithms for decision support (eg genetic and evolutionary programming), the computation of the most efficient paths (in terms of time, energy, etc.), the dynamic definition of optimization priorities, as well as aspects of resilience through automatic re-planning of the route in the event of interruptions on the predefined trajectory. For all that has been said so far, it is clear that the development of the AI will have consequences on the future organization of the armed forces, both for the conduct of the operations and for the structure and numbers of the defense sector. As in other areas subject to automation through the use of new digital technologies, even in the military one the human role of decision supervision, feedback and control of high-level operations will remain decisive for many years. At the same time, however, the need for training and specialization in line with the complete computerization will arise, with significant impacts in terms of information security (or cybersecurity), which will require increasingly specific skills. The fact that complete autonomy would be possible in the event of unavailability of personnel in control centers implies not only a higher level of security, but also the possibility of reducing organizational redundancies by dedicating resources to different and more specialized tasks. As already underlined, there are significant ethical and legal implications related to future decision-making processes for the choice of using force through a weapon system governed by an artificial intelligence, potentially endowed with a high level of autonomy. It is therefore essential to define clear and shared limitations and conditions of autonomy for the verifiability and traceability of the decision-making process. In particular, in order to govern decision-making and prevent ambiguities, it is essential to apply the well-known RACI (Responsible Accountable Consulted Informed) paradigm, which defines for each action who is responsible for its implementation, who is associated with its administrative / legal responsibility, who will have to be consulted for further information and possible approval, and finally who will have to be simply, but obligatorily, informed. All aspects related to international safety certifications that regulate design, development and verification of systems whose malfunctions can impact on the safety of people are also essential. Many of the current reference standards are no longer adequate if we consider the current and anticipated evolution of AI, and therefore they will have to be adjusted accordingly.

Place, publisher, year, edition, pages
Centro Alti Studi per la Difesa, 2018. p. 69
Keywords
CPS, cyber-physical systems, artificial intelligence, embedded systems, autonomous systems, military, defense applications
National Category
Embedded Systems
Research subject
Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-81015 (URN)978-88-99468-89-7 (ISBN)
Available from: 2019-03-08 Created: 2019-03-08 Last updated: 2019-03-14Bibliographically approved
Papp, J., Tokody, D. & Flammini, F. (2018). From traditional manufacturing and automation systems to holonic intelligent systems. In: Procedia Manufacturing: . Paper presented at 11th International Conference on Interdisciplinarity in Engineering, INTER-ENG 2017, University of Tirgu Mures, Romania; 5 - 6 October 2017 (pp. 931-935). Elsevier, 22
Open this publication in new window or tab >>From traditional manufacturing and automation systems to holonic intelligent systems
2018 (English)In: Procedia Manufacturing, Elsevier, 2018, Vol. 22, p. 931-935Conference paper, Published paper (Refereed)
Abstract [en]

In manufacturing and automation systems, there is an increasing need for switching to new paradigms instead of merely upgrading the technological systems. More specifically, manufacturing and automation systems should move towards holonic and intelligent paradigms, featuring a set of advantages with respect to legacy systems based on traditional approaches. In this position paper, we address those advantages and describe how to apply the basic principles of holonic systems in intelligent information systems with a focus on real-time applications. We also survey the basic concepts and reference taxonomy, providing an overview of the expected transition from traditional manufacturing and automation systems to holonic intelligent systems.

Place, publisher, year, edition, pages
Elsevier, 2018
Series
Procedia Manufacturing, ISSN 2351-9789
National Category
Embedded Systems
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-75269 (URN)10.1016/j.promfg.2018.03.132 (DOI)
Conference
11th International Conference on Interdisciplinarity in Engineering, INTER-ENG 2017, University of Tirgu Mures, Romania; 5 - 6 October 2017
Available from: 2018-06-07 Created: 2018-06-07 Last updated: 2019-03-06Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2833-7196

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