[hpc-announce] CfP: Safe, Secure and Robust AI @ SAC24

[Tommaso Zoppi]

(Apologies for cross-posting)

We are glad to announce the first edition of the Safe, Secure and Robust AI (S2RAI - SSRAI) track at the 39th ACM/SIGAPP Symposium On Applied Computing (SAC24) Conference (CORE B, approx 25% acceptance rate)

Conference will take place: Avila, Spain, 8-12 April 2024
Details here ->https://sites.google.com/view/s2rai-sac/
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Call for papers (PDF) is available at:https://tinyurl.com/s2rai-cfp2  

_*An overview: 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.

_*What are we looking for? 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.
_*How to Submit? Submission Guidelines*_
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
https://www.sigapp.org/sac/sac2024/authorkit.php.
- 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.

_*Where to Submit? Submission Links!*_
- Regular papers:https://www.sigapp.org/sac/sac2024/submission.php
- SRC papers:https://www.sigapp.org/sac/sac2024/submission_src.php
_*When to Submit? Important Dates*_
- September 15, 2023: Submission of regular papers and SRC research abstracts
- October 30, 2023: Notification of paper acceptance/rejection
- October 30, 2023: Notification of SRC acceptance/rejection
- November 30, 2023: Camera-ready copies of accepted papers/SRC

_*Who? Organizers*_
(Alphabetical order)
- Jeremie Guiochet (LAAS CNRS, University of Toulouse, France)
- Antonio Pecchia (University of Sannio, Italy)
- Maura Pintor (University of Cagliari, Italy)
- Tommaso Zoppi (University of Florence, Italy)
Should you have any questions, please mail tommaso<dot>zoppi<at>unifi<dot>it

_*Who? Technical Program Committee*_
(Alphabetical Order)
     Annalisa Appice (Università degli Studi di Bari Aldo Moro, Bari, Italy)
     Giovanni Apruzzese (University of Liechtenstein, Vaduz, Liechtenstein)
     Simon Burton (Fraunhofer, Munich, Germany)
     Giorgio Buttazzo (Scuola Superiore Sant'Anna, Pisa, Italy)
     Javier Carnerero Cano (Imperial College London, UK)
     Lorenzo Cavallaro (University College London, London, UK)
     Miguel Correia (INESC-ID, IST, University of Lisboa, Portugal)
     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)
     Nektaria Kaloudi (SINTEF Digital, Norway)
     Dan Kim (University of Queensland, Australia)
     Raphael Labaca-Castro (SandboxAQ, Munich, DE)
     Guanpeng Li (University of Iowa, Iowa - US)
     Fumio Machida (University of Tsukuba, Tsukuba, Japan)
     Ibéria Medeiros (University of Lisbon, Portugal)
     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)
     Paul Temple (Universiy of Rennes, CNRS, Inria, IRISA, France)
     Lishan Yang (George Mason University, Virginia, US)
     Marco Vieira (University of Coimbra, Coimbra, PT)