June 29, 2020
Workshops will run on June 29 in parallel with the Doctoral Forum and Tutorials. Information about workshops, including their respective programs, can be found hereafter:
The DSN Workshop on Dependable and Secure Machine Learning (DSML) is an open forum for researchers, practitioners, and regulatory experts, to present and discuss innovative ideas and practical techniques and tools for producing dependable and secure machine learning (ML) systems. A major goal of the workshop is to draw the attention of the research community to the problem of establishing guarantees of reliability, security, safety, and robustness for systems that incorporate increasingly complex ML models, and to the challenge of determining whether such systems can comply with the requirements for safety-critical systems. A further goal is to build a research community at the intersection of machine learning and dependable and secure computing.
The program of the workshop is available here.
Video of the session with Q&A
Welcome and Keynote 1
Dependability and security are of the utmost importance for computing systems. Due to the scale and complexity of current systems, both aspects are a permanent and growing concern in industry and academia. On the one hand, the volume and diversity of functional and non-functional data, including open source information, along with increasingly dynamical operating environments, create additional obstacles to the dependability and security of systems. On the other hand, it creates an information rich environment that, leveraged by techniques from modern data science, machine and statistical learning, and visualization, will contribute to improve systems resilience in contexts of dynamic operating environments and unexpected operating conditions. As such, there is a strong demand for production-ready systems leveraging from data-centric solutions able to improve and, adaptively, maintain the dependability and security of computing systems.
The workshop on Data-Centric Dependability and Security (DCDS) aims at providing researchers with a forum to exchange and discuss scientific contributions and open challenges, both theoretical and practical, related to the use of data-centric approaches that promote the dependability and cybersecurity of computing systems. We want to foster joint work and knowledge exchange between the dependability and security communities, and researchers and practitioners from areas such as machine and statistical learning, and data science and visualization. The workshop provides a forum for discussing novel trends in data-centric processing technologies and the role of such technologies in the development of resilient systems. It aims to discuss novel approaches for processing and analysing data generated by the systems as well as information gathered from open sources, leveraging from data science, machine and statistical learning techniques, and visualization. The workshop shall contribute to identify new application areas as well as open and future research problems, for data-centric approaches to system dependability and security.
The program of the workshop can be checked here.
Videos of the workshop sessions including Q&A
Welcome DCDS 2020 and Session 1: Keynote
Session 2: Network Security & Privacy
List of Papers in the session and their Teasers
A number of high-performance computing (HPC) commercial off-the-shelf (COTS) platforms offer the computation capabilities needed by autonomous systems in domains such as automotive, space, avionics, robotics and factory automation by means of multicores, GPUs and specialized accelerators. Unfortunately, the utilization of HPC platforms has been traditionally considered out of the reach for the safety-critical systems industry due to the difficulties or roadblocks these platforms bring to the certification process. This workshop focuses on the research towards the adoption of HPC hardware and software platforms in the context of safety- and security-critical applications. In particular, the scope of the workshop includes functional-safety and security requirements for HPC systems, including but not limited to non-functional aspects such as time predictability and energy consumption.
Topics of interest
- High-performance critical real-time systems
- Dependable systems and safety mechanisms
- Hardware and Software security in safety-critical systems
Carles Hernàndez (Universitat Politènica de València)
Jaume Abella (Barcelona Supercomputing Center)
Mikel Azkarate-askatsua (Ikerlan)
Roman Obermaisser (University of Siegen)
The program of the workshop can be checked here.
Video containing all workshop sessions
Over the last years, aerial and ground vehicles as well as mobile robot systems have been receiving an increased number of electronic components, connected through wireless networks and running embedded software. As processing power increases and software becomes more sophisticated, these vehicles gain the ability to perform complex operations, becoming more autonomous, safe, efficient, adaptable, comfortable and usable. These are known as Intelligent Vehicles.
This will be the sixth edition of the workshop, aiming at continuing the success of previous editions. The vast range of open challenges to achieve Safety and Security in Intelligent Vehicles (with or without connection with the Internet) is a fundamental reason that justifies the numerous research initiatives and wide discussion on these matters, which we are currently observing everywhere. Therefore, the workshop will keep its focus on exploring the challenges and interdependencies between security, real-time, safety and certification, which emerge when introducing networked, autonomous and cooperative functionalities.
AI and Reliability Trends in Safety Critical Autonomous Systems on Ground and AirJyotika Athavale (Intel), Michael Paulitsch (Intel), Andrea Baldovin (Intel), Ralf Graefe (Intel), and Rafael Rosales (Intel)
Reward Tuning for self-adaptive Policy in MDP based Distributed Decision-Making to ensure a Secure Mission PlanningMohand Hamadouche (Lab-STICC, CNRS), Catherine Dezan (Lab-STICC, CNRS), and Kalinka Regina Lucas Jauqie Castelo Branco (Universidade de Sao Paulo)
The Quantitative Risk Norm - A Proposed Tailoring of HARA for ADSFredrik Warg (RISE Research Institutes of Sweden), Rolf Johansson (Autonomous Intelligent Driving), Martin Sanfridson (Volvo Technology AB), Mattias Brännström (Zenuity AB), Magnus Gyllenhammar (Zenuity AB), Martin Skoglund (RISE Research Institutes of Sweden) and Anders Thorsén (RISE Research Institutes of Sweden)
Analysis of Cybersecurity Mechanisms with respect to Dependability and Security AttributesBehrooz Sangchoolie (Dependable Transport Systems, RISE Research Institutes of Sweden), Peter Folkesson (Dependable Transport Systems, RISE Research Institutes of Sweden), Pierre Kleberger (Dependable Transport Systems, RISE Research Institutes of Sweden) and Jonny Vinter (Dependable Transport Systems, RISE Research Institutes of Sweden)
Exploring Fault Parameter Space using Reinforcement Learning-based Fault InjectionMehrdad Moradi (University of Antwerp and Flanders Make vzw), Bentley James Oakes (University of Antwerp and Flanders Make vzw), Mustafa Saraoglu (Technische Universitat Dresden), Andrey Morozov (Technische Universitat Dresden), Klaus Janschek (Technische Universitat Dresden) and Joachim Denil (University of Antwerp and Flanders Make vzw)
Flexible Deployment and Enforcement of Flight and Privacy Restrictions for Drone ApplicationsNasos Grigoropoulos (University of Thessaly) and Spyros Lalis (University of Thessaly)
Conceptual Design of Human-Drone Communication in Collaborative EnvironmentsHans Dermot Doran (Institute of Embedded Systems, ZHAW), Monika Reif (Institute of Applied Mathematics and Physics, ZHAW), Marco Oehler (Zurich University of Applied Sciences), Curdin Stöhr (Zurich University of Applied Sciences), and Pierluigi Capone (Centre for Aviation, ZHAW).
A hierarchical fault tolerant architecture for an autonomous robotFavier Anthony (LAAS-CNRS, INPT ENSEEIHT - University of Toulouse), Messioux Antonin (LAAS-CNRS, INPT ENSEEIHT, University of Toulouse), Jérémie Guiochet (LAAS-CNRS,UPS, INPT, University of Toulouse), Jean-Charles Fabre (LAAS-CNRS, UPS, INPT, University of Toulouse) and Charles Lesire (ONERA/DTIS, University of Toulouse).
"Future Challenges in Safety and Security of Intelligent Vehicle"
- Mario Trapp (Fraunhofer IKS, Germany)
- Sibin Mohan (University of Illinois, USA)
- Miriam Gruber (BMW, Germany)
- Behrooz Sangchoolie (RISE, Sweden)