CPS

Cyber-Physical Systems

Members of the CPS group involved in developing a national-level cybersecurity course

2020-03-08

The proposal for development of Module C11 “Cyber Security, Industrial Data Protection and Data Integrity” by host institution Mälardalen University in cooperation with Linnaeus University (CPS research group: Francesco Flammini – project leader, and Ola Flygt), RISE and several industry representatives from Combitech, Bombardier Transportation and Westermo, has been accepted for funding within the Civilingenjör4.0 initiative (Industry 4.0 – Cyber-physical production systems and connected industry).

Further information at:

https://www.civing4.se/

(image source: Wikimedia Commons)

Seminar on Performance Engineering Cyber-Physical Systems

2019-12-06

We would like to thank our new research assistant Lorenzo Pagliari for the seminar he held this morning (December 6th 2019, 9.00-10.00) in Växjö campus about “Performance Engineering Cyber-Physical Systems“.

Please find below the abstract and the slides of his talk.

 

Abstract:

Cyber-Physical Systems (CPS) are the consequence of today’s technology progression. They were born as natural evolution of a very large family of systems such as embedded systems, complex systems and system of systems and many others. Technology improvements give us more computational power, more powerful telecommunication architectures and more efficient software and algorithms that characterize the smart feature that is so widespread and used in the last few years. New terms such as “smart robots”, “smart industry”, “smart automotive” are becoming more popular and widespread used. Besides that, all these new type of systems are attracting more and more attention of the respective research communities. Therefore, with a new type of system that is strongly impacting many different realities, the importance of performance engineering them properly is rising.

SLIDES: Pagliari_PerformanceEngineering_CPS

 

If you have any questions, please feel free to contact him or Mauro Caporuscio.

Project RAILS (Roadmaps for AI integration in the raiL Sector) selected for EU funding (Horizon2020 – Shift2Rail JU)

2019-11-12

The research project named RAILS (Roadmaps for AI integration in the raiL Sector) has been selected for EU funding by the Horizon 2020 Shift2Rail Joint Undertaking (call ID: S2R-OC-IPX-01-2019). The project will be in cooperation between Linnaeus University, Italian Interuniversity Consortium for Informatics (CINI), Delft University of Technology, University of Leeds, and will leverage on the input from big industry players like Hitachi Rail STS.

 

PROJECT ABSTRACT

The overall objective of the RAILS research project is to investigate the potential of Artificial Intelligence (A.I.) approaches in the rail sector and contribute to the definition of roadmaps for future research in next generation signalling systems, operational intelligence, and network management. RAILS will address the training of PhD students to support the research
capacity in A.I. within the rail sector across Europe by involving research institutions in four different countries with a combined background in both computer science and transportation systems. RAILS will produce knowledge, ground breaking research and experimental proof-of-concepts for the adoption of A.I. in rail automation, predictive maintenance and defect detection, traffic planning and capacity optimization. To that aim, RAILS will combine A.I. paradigms with the Internet of Things, in order to leverage on the big amount of data generated by smart sensors and applications. The research activities will be conducted in continuity with ongoing research in railways, but the methodological and technological concepts developed in RAILS are expected to stimulate further innovation providing new research directions to improve reliability, maintainability, safety, security, and performance. With respect to safety, emerging threats and certification issues will be addressed when adopting A.I. in autonomous and cooperative driving, based on the concepts of “explainable A.I.” and “Trustworthy AI”. With respect to cyber-physical threat detection, innovative approaches will be developed based on A.I. models like Artificial Neural Networks and Bayesian Networks together with multi-sensor data fusion and artificial vision. Resilience and optimization techniques based on genetic algorithms and self-healing will be addressed to face failures and service disruptions as well as to increase efficiency and line capacity. All those techniques will pave the way to the development of the new “Railway 4.0”.

RAILS_leaflet_final

LNU Project Page

CORDIS Page

RAILS Project Website

Paper on Data-Driven Fault Diagnosis to be presented at 4th International Conference on System Reliability and Safety (sponsored by IEEE)

2019-11-04

The paper entitled “Data-Driven Fault Diagnosis of Once-Through Benson Boilers” (Mehdi Saman Azari, Francesco Flammini, Stefania Santini, Mauro Caporuscio) will be presented at the 4th International Conference on System Reliability and Safety (ICSRS’19), sponsored by the IEEE, which will be held in Rome (Italy) on November 20-22, 2019.

The new PhD student Mehdi Saman Azari will attend the conference and present the paper, which will be published in the IEEE Digital Library.

Congratulations to Mehdi for his first paper as a PhD student at LNU!

 

Abstract

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 scenarios.

 

UPDATE February 17th 2020

The paper is now available in the IEEE Digital Library and accessible at the following link:

https://ieeexplore.ieee.org/document/8987699

 

Study on smart-troubleshooting accepted for publication on top Elsevier journal

2019-09-08

The paper entitled “Smart-Troubleshooting Connected Devices: Concept, Challenges and Opportunities” (Mauro Caporuscio, Francesco Flammini, Narges Khakpour, Prasannjeet Singh, Johan Thornadtsson) has been accepted for publication on Future Generation Computer Systems (Elsevier, Impact Factor: 5.768). The paper includes the results achieved during the SEED project entitled Smart-Troubleshooting in the Connected Society in cooperation with Sigma Technology, and addresses several challenges towards self-healing for resilient IoT.

 

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.

Digital Object Identifier:

https://doi.org/10.1016/j.future.2019.09.004

Track leader at ESREL2020-PSAM15

2019-08-15

ESREL2020-PSAM15 combines the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference, and will be held in Venice, Italy, on June 21–26, 2020. It will be a unique World Exposition (a real “Expo Tech”) of scientific methodologies and technical solutions for the reliable design and operation of components and systems, for the prevention and management of risk in complex systems and critical infrastructures.

Francesco Flammini has been invited to be the Track Leader (TL) to coordinate the peer review process for the papers submitted to the track “Smart Devices and Systems Reliability” for the ESREL2020-PSAM15 Conference.

As a Track Leader he will act like guest editor in the reviewing process for the specific track. In this role he will;

  • assign reviewers to the papers submitted to the track
  • provide feedback to the authors
  • take the final decision on the acceptance/rejection of the paper.

For more information about the conference – visit the conference website.

Research on intelligent cybersecurity at IEEE SMC 2019

2019-07-29

The paper entitled “A Review of Intelligent Cybersecurity with Bayesian Networks” (Mauro Pappaterra, Francesco Flammini) has been accepted for conference presentation and publication in the proceedings of the 2019 IEEE SMC international conference, i.e. the flagship event of the  IEEE Systems, Man and Cybernetics society, special session on Homeland Security: Tools and Methodologies.

The paper will be presented by master student Mauro Pappaterra, who has been granted registration costs and travel expenses by the Department of Computer Science and Media Technology.

 

Abstract

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.

See also:

https://lnu.se/en/meet-linnaeus-university/current/news/2019/research-on-intelligent-cyber-security-to-be-presented-at-ieee-conference/

 

UPDATE, August 20th 2019

Mauro has also been selected as “Student or Young Professional Travel Grant Winner” for the SMC 2019 conference.

 

UPDATE, October 7th 2019

A picture of Mauro’s presentation:

 

UPDATE, December 2nd 2019

The paper is finally available from IEEE Digital Library at the following link:

https://ieeexplore.ieee.org/document/8913864

Plain text citation:

M. J. Pappaterra and F. Flammini, “A Review of Intelligent Cybersecurity with Bayesian Networks,” 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Bari, Italy, 2019, pp. 445-452.
doi: 10.1109/SMC.2019.8913864
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8913864&isnumber=8913838

Pioneering research on Virtual Coupling published on top IEEE journal

2019-07-24

The paper entitled “ERTMS/ETCS Virtual Coupling: Proof of Concept and Numerical Analysis”, describing a pioneering research developed in cooperation between LNU and the University of Naples Federico II, has been accepted for publication on the top journal about smart-transportation, i.e. “IEEE Transactions on Intelligent Transportation Systems”.

The paper can be accessed online from the following link:

https://ieeexplore.ieee.org/document/8737771

 

Abstract:

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.

IoT tech day August 29th

2019-06-26

Who said that Internet of Things has to be difficult? Linnaeus University and Kalmar Energi invites you to an inspirational day with the theme IoT. The researchers from the CPS-group are co-organizing the event.

During the inspirational day, we will showcase various uses and give ideas for new business opportunities using Internet of Things. This is interesting not least because it is now possible to use an open IoT network in Kalmar to freely test and develop.

The IoT technology is now so simple and, most importantly, cheap that all that is required is a little time and interest in turning ideas into reality.

The inspirational day will also be broadcast live on the Internet. The link will be announced later. The presentations will be held in both Swedish and English.

For more information about the program, speakers, how to register and the follow-up workshops please see the event website.

//Diana

 

UPDATE August 30th 2019

Pictures taken from the talk of the invited speaker Dr. Usman Raza (Principal Research Engineer, Toshiba Research Europe Ltd)

Slides about IoT Research & Education at LNU:

Flammini_IoT_Kalmar_2019

Post-Event News (in Swedish)

Talk: Towards Secure Architectural Adaptation at SEAMS 2019

2019-05-26

A few of our researchers are now in Montreal, Canada for SEAMS 2019 (Symposium on Software Engineering for Adaptive and Self-Managing Systems 2019 conference). The objective of SEAMS is to bring together researchers and practitioners from diverse areas to investigate, discuss, and examine the fundamental principles, the state of the art, and critical challenges of engineering self-adaptive and self-managing systems.

On Sunday May 26th, Narges Khakpour will give a presentation of the paper entitled Towards Secure Architectural Adaptation (authored by: Narges Khakpour, Charilaos Skandylas, Goran Saman Nariman, and Danny Weyns), accepted for publication in the book of proceedings of the conference.

As any software system, a self-adaptive system is subject to security threats. However, applying self-adaptation may introduce additional threats. So far, little research has been devoted to this important problem. In this paper, we propose an approach for vulnerability analysis of architecture-based adaptations in self-adaptive systems using threat modeling and analysis techniques. To this end, we specify components’ vulnerabilities and the system architecture formally and generate an attack model that describes the attacker’s strategies to attack the system when adaptation is applied by exploiting different vulnerabilities. We use a set of security metrics to quantitatively assess the security risks of adaptations based on the produced attack model which enables the system to consider security aspects while choosing an adaptation to apply to the system. We automate and incorporate our approach into the Rainbow framework, allowing for secure architectural adaptations at runtime. To evaluate the effectiveness of our approach, we apply it on a simple document storage system and on the ZNN system.

For more information please click here.