2022-12-09
Lorenzo De Donato, a visiting PhD student from University of Naples Federico II, is currently visiting LNU due to EU RAILS project funding.
He has presented a poster at the LNU Big Data Conference (see photo below) and given a specific research seminar about his most recent research within the project.
2022-09-13
We are pleased to announce that the paper entitled “Railway Digital Twins and Artificial Intelligence: Challenges and Design Guidelines“, whose main author is LNU student Ruth Dirnfeld, has been published on the Springer book of proceedings of the AI4RAILS workshop. We congratulate Ruth for her second international publication, which demonstrates her capability to develop novel and interesting contributions. The work has been carried on within the RAILS EU funded research project.
2021-01-21
We are glad to announce this new paper published on a top IEEE open access journal (Impact Factor: 3.7, Scimago Journal Rank: Q1 Computer Science).
The paper is co-authored by Nijat Rajabli, Francesco Flammini, Roberto Nardone and Valeria Vittorini and it is a literature review on the software Verification and Validation (V&V) of safe autonomous cars. The paper is a result of the outstanding job done by Nijat, a Linnaeus University student, during his project work for the course of Current Topics in Computer Science.
We believe that due to its quite extensive topic coverage, the paper can serve as a useful compendium for the many engineers and researchers who are starting to investigate those extremely current and challenging subjects related to the software safety of autonomous road vehicles.
Please find below more detailed information about the paper.
N. Rajabli, F. Flammini, R. Nardone and V. Vittorini, “Software Verification and Validation of Safe Autonomous Cars: A Systematic Literature Review,” in IEEE Access, vol. 9, pp. 4797-4819, 2021, doi: 10.1109/ACCESS.2020.3048047.
Abstract: Autonomous, or self-driving, cars are emerging as the solution to several problems primarily caused by humans on roads, such as accidents and traffic congestion. However, those benefits come with great challenges in the verification and validation (V&V) for safety assessment. In fact, due to the possibly unpredictable nature of Artificial Intelligence (AI), its use in autonomous cars creates concerns that need to be addressed using appropriate V&V processes that can address trustworthy AI and safe autonomy. In this study, the relevant research literature in recent years has been systematically reviewed and classified in order to investigate the state-of-the-art in the software V&V of autonomous cars. By appropriate criteria, a subset of primary studies has been selected for more in-depth analysis. The first part of the review addresses certification issues against reference standards, challenges in assessing machine learning, as well as general V&V methodologies. The second part investigates more specific approaches, including simulation environments and mutation testing, corner cases and adversarial examples, fault injection, software safety cages, techniques for cyber-physical systems, and formal methods. Relevant approaches and related tools have been discussed and compared in order to highlight open issues and opportunities.
Keywords: Vehicles; Autonomous automobiles; Safety; Software; Accidents; Roads; Systematics; Advanced driver assistance systems; automotive engineering; autonomous vehicles; cyber-physical systems; formal verification; intelligent vehicles; machine learning; system testing; system validation; vehicle safety
URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9310181&isnumber=9312710
2020-09-23
https://sites.google.com/view/ai4rails/home-page
The Springer proceedings of AI4RAILS are available at:
Finally, the paper entitled “Low-Power Wide-Area Networks in Intelligent Transportation: Review and Opportunities for Smart-Railways”, co-authored with Linnaeus University master student Ruth Dirnfeld, has been recently presented at the 23rd IEEE International Conference on Intelligent Transportation Systems (ITSC) according to the following updated program:
https://its.papercept.net/conferences/conferences/ITSC20/program/ITSC20_ContentListWeb_3.html
Presentation slides are available on slideshare.
Any feedback on all those initiatives and preliminary results is very much appreciated!
Prof. Francesco Flammini
RAILS Technical Manager, AI4RAILS Co-Chair
2020-07-11
Congratulations to Charilaos, Narges and Jesper for their paper being accepted at the 1st IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2020)!
Please find below additional information about their research.
Title: Self-Adaptive Trust-Aware Decentralized Information Flow Control
Authors: Charilaos Skandylas, Narges Khakpour, Jesper Andersson
Abstract:
Modern software systems and their corresponding
architectures are decentralized, distributed, and dynamic. As
a consequence, decentralized mechanisms are also required to
ensure security in such architectures. Decentralized Information
Flow Control (DIFC) is a mechanism to control information
flow in distributed systems. However, DIFC mechanisms require
the resolution of specific centralized control and trust issues. In
this paper, we propose an adaptive, trust-aware, decentralized
information flow approach that incorporates trust in DIFC for
decentralized systems. We employ decentralized feedback loops
to enable decentralized control and adaptive trust assignments.
In our approach, adaptivity mitigates two aspects of systems
dynamics that cause uncertainty: the ever-changing nature of
trust and the system openness. We formalize our trust-aware
DIFC model and instantiate two decentralized feedback loop
architectures to implement it. We discuss the design and implementation
considerations and evaluate the effectiveness of
adaptive trust-aware DIFC on a set of decentralized architectures
and a microservices-based system.
2020-06-05
I am glad that our students continue to collaborate with us and succeed years after their graduation. I would like to congratulate Mauro José Pappaterra – whom I have supervised at Linnaeus University and is now studying at Uppsala University – for this recent achievement: the chapter entitled “Bayesian Networks for online threat detection” (co-authored by Mauro and myself) has been accepted for inclusion in the upcoming book entitled “Machine Intelligence and Big Data Analytics For Cybersecurity Applications” to be published by Springer Nature in book series “STUDIES IN COMPUTATIONAL INTELLIGENCE”. The chapter extends the research started with:
https://lnkd.in/eSvVeHX
Mauro is also involved in the #railsproject contributing to deliverable D1.1 about AI and railway taxonomy with materials developed in its master’s thesis.
#artificialintelligence #cybersecurity #bayesnetworks
UPDATE DECEMBER 21ST 2020
Paper now available at:
https://link.springer.com/chapter/10.1007/978-3-030-57024-8_6
2020-05-22
In the last few weeks, we started to reap the benefits of our hard work with two good news. The paper entitled “Safety Integrity Through Self-Adaptation for Multi-Sensor Event Detection: Methodology and Case-Study” (with Stefano Marrone, Roberto Nardone, Mauro Caporuscio and Mirko D’Angelo) has been accepted with minor revisions by Future Generation Computer Systems (Elsevier, IF: 5.768), while the paper entitled “Low-Power Wide-Area Networks in Intelligent Transportation: Review and Opportunities for Smart-Railways” (with Ruth Dirnfeld, Stefano Marrone, Roberto Nardone and Valeria Vittorini) has been accepted for presentation at the 23rd IEEE International Conference on Intelligent Transportation Systems, i.e., the top event on intelligent transportation.
#railsproject #safety #its #iot #autonomousvehicles #smart #railways
UPDATE JUNE 27th 2020
FGCS paper finally online at:
https://www.sciencedirect.com/science/article/abs/pii/S0167739X19333734
2020-04-14
An overview article about the H2020 RAILS Research Project has been recently published on ERCIM News:
https://ercim-news.ercim.eu/en121/r-i/roadmaps-for-ai-integration-in-the-rail-sector-rails
2020-04-06
The paper entitled “Towards Self-Healing in the Internet of Things by Log Analytics and Process Mining” (Singh PJ. Flammini F, Caporuscio M, Saman Azari M, Thornadtsson J) has been accepted for presentation at the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020-PSAM15), to be held in Venice, Italy on June 21-26 2020, and publication in the conference book of proceedings.
Link to the paper on Researchgate:
UPDATE November 2020:
2020-03-19
Organizers:
Workshop chairs: Stefano Marrone (University of Naples Federico II, Naples, Italy), Roberto Nardone (Mediterranean University of Reggio Calabria, Reggio Calabria, Italy)
Workshop series steering committee chairs: Francesco Flammini (Mälardalen University and Linnaeus University, Sweden), Valeria Vittorini (University of Naples Federico II, Naples, Italy)
The impact of Artificial Intelligence (AI) techniques on industry has been so disruptive that it gave rise to a new wave of research and applications. Several industries, mainly in logistics and manufacturing, have benefited significantly from AI adoption and this positive trend is planned to be kept in the future. Modern and future railways represent one of the fields in which AI is expected to have a significant impact in a medium to long term perspective, in order to get higher levels of automation. On the one hand, this opens for unprecedented scenarios for railway systems, but on the other hand, it also raises concerns regarding system dependability and new threats associated with a high level of autonomy. Therefore, the first step towards the adoption of AI in the railway sector is understanding to what extent AI can be considered reliable, safe and secure. In such a context, building upon the ongoing Shift2Rail project RAILS (Roadmaps for the AI integration in the raiL Sector), the aim of the 1st AI4RAILS workshop is to provide a forum for researchers, practitioners and business leaders to discuss and share new perspectives, ideas, technologies and solutions for an effective and dependable integration of AI techniques in rail-based transportation systems.
Co-located with 16th European Dependable Computing Conference, 7-10 September 2020, Munich, Germany:
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