Call for Papers:
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.
Topics of Interest:
- Testing, certification, and verification of ML models and algorithms
- Metrics for benchmarking the dependability and security of ML systems
- Adversarial machine learning (an emphasis will be put on defenses)
- Resilient and repairable ML models and algorithms, including mechanisms for failsafe defaults and smooth degradation of performance
- Reliability and security of ML architectures, computing platforms, and distributed systems
- Faults in implementation of ML algorithms and their consequences
- Dependability of ML accelerators and hardware platforms
- Safety and societal impact of machine learning
- Testing, certification, and verification of ML models and algorithms
Important dates:
- Website opens for Submission: Feb 6, 2023 (AOE)
- Submission Deadline: March 31, 2023 (AOE)
- Notification of Acceptance: April 21, 2023
- Camera Ready: May 5, 2023
- Workshop: June 27, 2023
Submissions:
DSML welcomes both research papers reporting results from mature work, and more speculative papers describing new ideas with preliminary exploratory work. Papers reporting industry experiences, case studies, and datasets will also be encouraged. This year, we are also soliciting proposals for research talks based on work previously published elsewhere (reference to previous work is required). We strongly encourage these research talks to also include new ideas and provocative opinions and not just summarize previous work that is already published. Specifically, we accept submissions in the following formats:
- Regular research papers (up to 6 pages + 3 pages for references and supplementary material)
- Proposals for research talks (1 page + 3 pages for references and supplementary material)
All submissions should be in PDF format and must adhere to the IEEE Computer Society 8.5x11 two-column camera-ready format (using a 10-point font on 12-point single-spaced leading). Both LaTeX and MS Word templates are available here: https://www.ieee.org/conferences_events/conferences/publishing/templates.html
We will use a double-blind review process only for the regular research papers, so the authors must anonymize their submissions. The first page must include the title of the paper, but no information on authors names and affiliations. Research talks need not be anonymous.
Submission site: https://dsml23.hotcrp.com/
Proceedings:
Authors of regular papers can select either of the following options for the publication of their accepted papers:
(1) Paper will appear in the supplementary DSN proceedings (archived in the IEEE Digital library), with the same page limit constraints as specified above,
(2) Only an extended abstract (up to 2 pages + 3 pages for references and supplementary material) of the paper will be included in the supplementary DSN proceedings, but the authors are required to post a full version of the paper on arxiv that will be linked from the workshop website.
General and PC Chairs:
Lishan Yang, George Mason University
Matthew Jagielski, Google Research
Steering Committee:
Homa Alemzadeh, University of Virginia
Rakesh Bobba, Oregon State University
Varun Chandrasekaran, Microsoft Research & University of Illinois Urbana-Champaign
David Evans, University of Virginia
Nicolas Papernot, University of Toronto & Vector Institute
Karthik Pattabiraman, University of British Columbia
Florian Tramèr, ETH Zurich
Program Committee:
Vincent Bindschaedler, University of Florida
Siva Hari, Nvidia
Sanghyun Hong, Oregon State University
Fumio Machida, University of Tsukuba
George Papadimitriou, University of Athens
Kexin Pei, Columbia University
Jonathan Petit, Qualcomm
Uttam Thakore, Meta
Hui Xu, Fudan University
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