S2RAI

Updates and Announcements

• 2024/04/10: S2RAI took place in Avila!

• 2024/02/14: S2RAI program is online

• 2023/11/24: Notifications are out!

• 2023/09/29: deadline extension! Submission deadline is now set to October, 6th

• 2023/08/16: updated CfP!

• 2023/07/11: (Almost) Final TPC and first CfP are Online!

• 2023/06/21: Submission Information and first batch of TPC members are online.

• 2023/05/31: Track website is OUT!

Track Abstract

Machine Learning (ML) became the enabling technology of several applications. There is an enormous interest in adopting them to support critical tasks such as error/intrusion/anomaly detection, image classification or even object detection and trajectory planning to support autonomous driving. However, components that operate in critical systems must be assessed so that the encompassing system complies with adequate safety and security requirements before they are deployed and used in their operational environment without generating catastrophic hazards to the health of citizens, the environment, or the infrastructures. The absence of safety/security guarantees, or even a quantitative estimation of their robustness against specific events (e.g., unknown or zero-day attacks, adversarial attacks, out-of-distribution data) may be considered unacceptable by certification bodies, holding their deployment into real critical systems.

Main Topics

Unfortunately, the current maturity of research is still far from guaranteeing a safe, secure and robust operation of ML algorithms in many domains. Therefore, this track calls for contributions that aim at making a step towards a safe, secure and robust operation of ML components through (non-exhaustive list):

• the definition of architectural patterns (e.g., safety monitors or safety wrappers), software mechanisms, model-based analyses, and metrics aiming at a safe operation of ML algorithms;

• the proposal or experimental evaluation of defenses against adversarial attacks or any potential threat to ML algorithms themselves;

• techniques to make ML algorithms robust against unknown, out-of-distribution data, and their evaluation in simulated environments or in the wild;

• methods for explainable AI, their evaluation, comparison and applicability to critical systems;

• frameworks or mechanisms to precisely compute the confidence in the prediction of ML algorithms, and use them to build a safe, secure or robust ML-based component;

• methodologies or data-driven processes that aim at guiding the integration of ML algorithms in critical systems such that safety and security requirements of the encompassing systems can be guaranteed.

Program

7 papers were accepted for presentation at S2RAI @ SAC24. S2RAI will take place on Wednesday, April 10th, at Avila, Spain.

First session: Safe and Robust AI (9.30 - 11.00)

• Data Poisoning Detection in Federated Learning (Denise-Phi Khuu, Michael Sober, Dominik Kaaser, Mathias Fischer and Stefan Schulte)

• Validation of Safety Metrics for Object Detectors in Autonomous Driving (Andreas Rønnestad, Andrea Ceccarelli and Leonardo Montecchi)

• Can you trust your Agent? The Effect of Out-of-Distribution Detection on the Safety of Reinforcement Learning Systems (Tom Haider, Karsten Roscher, Benjamin Herd, Felippe Schmoeller Roza and Simon Burton)

• Can you trust your ML metrics? Using Subjective Logic to determine the true contribution of ML metrics for safety (Benjamin Herd and Simon Burton)

Second Session: Secure AI and Federated Learning (11.30 - 13.00)

• Multi-Confederated Learning: Inclusive Non-IID Data handling with Decentralized Federated Learning (Michael Duchesne, Kaiwen Zhang and Talhi Chamseddine)

• Understanding the Process of Data Labeling in Cybersecurity (Tobias Braun, Irdin Pekaric and Giovanni Apruzzese)

• Deceptive Skies: Leveraging GANs for Drone Sensor Data Falsification (Mehmed Uludag, Maryna Veksler, Yasin Yilmaz and Kemal Akkaya)

Submission Gudelines

Paper Format

SAC (and thus S2RAI) accepts to types of submissions: regular papers and SRC Abstracts. The review process is double-blind: please prepare your paper accordingly. You can download the official Autor Kit from here.

Regular papers: the total number of pages allowed with your registration without any extra page fee is eight (8). See the SAC 2024 website registration page for additional page charges. A maximum of 10 (first 8 pages no extra fees, 2 extra pages with fees) is allowed for each regular paper. Latex Template, Word Template.

Student Research Track (SRC) Abstracts: the total number of pages allowed with your registration is four (4). No extra pages. Latex Template, Word Template. The conference provides travel grants for PhD students, check here for further information.

Note that those page limits include references.

Submission Links

Regular papers: click here!

SRC papers: click here!

Important Dates

• October, 6th, 2023 GMT-7 (extended!): Submission of regular papers and SRC research abstracts

• November 24th, 2023: Notification of paper acceptance/rejection

• November 24th, 2023: Notification of SRC acceptance/rejection

• December 31st, 2023: Camera-ready copies of accepted papers/SRC

• December 31st, 2023: Author registration due date

• April 9, 2024: SRC Posters Exhibit

• April 10, 2024: Non-SRC Posters Program

• April 11, 2024: SRC Oral Presentations

Disclaimer

Paper registration is required, allowing the inclusion of the paper/poster in the conference proceedings. An author or a proxy attending SAC MUST present the paper paying a full conference fee. This is a requirement for the paper/poster to be included in the ACM digital library. No-show of registered papers and posters will result in excluding them from the ACM digital library.

Organization

Track Chairs

• Jeremie Guiochet (LAAS CNRS, University of Toulouse, France)

• Antonio Pecchia (University of Sannio, Italy)

• Maura Pintor (University of Cagliari, Italy)

• Tommaso Zoppi (University of Trento, Italy)

Should you have any questions, please mail tommaso<dot>zoppi<at>unitn<dot>it

Technical Program Committee of S2RAI

• Daniele Angioni (University of Cagliari, Italy)

• Annalisa Appice (Università degli Studi di Bari Aldo Moro, Bari, Italy)

• Giovanni Apruzzese (University of Liechtenstein, Vaduz, Liechtenstein) 

• Muhammad Atif (University of Florence, Italy)

• Simon Burton (Fraunhofer, Munich, Germany)

• Giorgio Buttazzo (Scuola Superiore Sant'Anna, Pisa, Italy)

• Javier Carnerero Cano (Imperial College London, UK)

• Daniel Casini (Scuola Superiore Sant'Anna, Pisa, Italy)

• Marta Catillo (University of Sannio, Italy)

• Lorenzo Cavallaro (University College London, London, UK)

• Zakaria Chihani (CEA, France)

• Andrew Cullen (University of Melbourne, Australia)

• Andrea Del Vecchio (University of Sannio, Italy)

• Luca Demetrio (University of Genova, Genova, Italy)

• Thorsten Eisenhofer (Ruhr University Bochum, Bochum, Germany)

• Francesco Flammini (IDSIA USI-SUPSI and Mälardalen University, Mälardalen, Sweden)

• Simos Gerasimou (University of York, York, UK)

• Joris Guerin (Espace-Dev, IRD, Montpellier, France)

• Kassem Kallas (INRIA, Rennes, France)

• Nektaria Kaloudi (SINTEF Digital, Norway)

• Dan Kim (University of Queensland, Australia)

• Raphael Labaca-Castro (SandboxAQ, US)

• Guanpeng Li (University of Iowa, Iowa - US)

• Fumio Machida (University of Tsukuba, Tsukuba, Japan)

• Ibéria Medeiros (University of Lisbon, Portugal)

• Chokri Mraidha (CEA LIST, Paris-Saclay University, France)

• Biagio Montaruli (SAP and EUROCOM, France)

• Leonardo Montecchi (Norwegian University of Science and Technology, Trondheim, Norway)

• Karthik Pattabiraman (University of British Columbia, Vancouver, Canada)

• Adìn Ramìrez Rivera (University of Oslo, Norway)

• Vera Rimmer (DistriNet, KU Leuven, Belgium)

• Angelo Sotgiu (CINI / University of Cagliari, Italy )

• Paul Temple (Universiy of Rennes, CNRS, Inria, IRISA, France)

• Lishan Yang (George Mason University, Virginia, US)

• Marco Vieira (University of Coimbra, Coimbra, PT)