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DSML 2021 : 4th International Workshop on Dependable and Secure Machine Learning

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Link: https://dependablesecureml.github.io
 
When Jun 21, 2021 - Jun 21, 2021
Where Taiwan
Submission Deadline Mar 28, 2021
Notification Due Apr 11, 2021
Final Version Due Apr 18, 2921
Categories    dependable system   machine learning   software reliability   software engineering
 

Call For Papers

FOURTH INTERNATIONAL WORKSHOP ON DEPENDABLE AND SECURE MACHINE LEARNING (DSML 2021)
Co-located with the 51th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2021)
21 June 2021, Taipei, Taiwan
Due to COVID-19, this year's workshop will be held virtually.
https://dependablesecureml.github.io

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 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 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. This will be the fourth edition of the workshop.

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 placed 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

IMPORTANT DATES (AOE):
- Website open for Submission: 15 Feb, 2021 (AOE)
- Submission Deadline: 22 March, 2021 (AOE)
- Notification of Acceptance: 11 April, 2021
- Camera Ready: 18 April, 2021
- Workshop: 21 June, 2021

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 will 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 anonymized though.

Submission site: https://dsn-dsml21.hotcrp.com/

All submitted manuscripts will be peer-reviewed by the program committee. Papers will be accepted and included in the workshop program according to the following criteria: relevance of the addressed topic to the scope of the workshop; novelty and value of the proposed contribution; scientific merit; quality of the writing, presentation accuracy and style.


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.

Organizing Committee:
- Homa Alemzadeh, University of Virginia
- Rakesh Bobba, Oregon State University
- Varun Chandrasekaran, University of Wisconsin-Madison
- David Evans, University of Virginia
- Nicolas Papernot, University of Toronto & Vector Institute
- Karthik Pattabiraman, University of British Columbia
- Florian Tramèr, Stanford University
- Guanpeng(Justin) Li, University of Iowa
- Hui Xu, Fudan University

Program Committee:
- Fabio Pierazzi, King's College London
- Neil Gong, Duke University
- Nirupam Gupta, Georgetown University
- Trinabh Gupta, University of California Santa Barbara
- Pinjia He, ETH Zürich
- Dong Seong Kim, University of Queensland
- Amir Rahmati, Stony Brook University
- Timothy Tsai, Nvidia
- Xin Zhang, Peking University
- Yao-Tung Tsou, Feng Chia University


Important Announcement:
Due to COVID-19, this year's workshop will be held virtually. We will be making accommodations for virtual presentations. The detailed information will be shared later. Submission of a paper indicates the willingness to attend the workshop and present it.

Links:
------
[1] https://dependablesecureml.github.io
[2] https://dsn-dsml21.hotcrp.com/

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