Kyoto, Japan | 19 June, 2023
Call for Papers
5th ACNS Workshop on Security in Machine Learning and its Applications (SiMLA 2023)
Co-located with ACNS 2023: 21st International Conference on Applied Cryptography and Network Security
IMPORTANT DATES
Paper submission deadline: March 9, 2023 (Anywhere on Earth)
Acceptance Notification: April 19, 2023
Camera-ready deadline: May 1, 2023 (Anywhere on Earth)
SiMLA Conference: 19 June, 2023 (15:30 - 18:30 JST (UTC+9))
AIMS AND SCOPE
As the development of computing hardware, algorithms, and more importantly, the availability of a large volume of data grows, machine learning technologies have become increasingly popular. Practical systems have been deployed in various domains, like face recognition, automatic video monitoring, and even auxiliary driving. However, the security implications of machine learning algorithms and systems are still unclear. For example, developers still lack a deep understanding of adversarial machine learning, one of the unique vulnerabilities of machine learning systems, and are unable to evaluate the robustness of those machine learning algorithms effectively. The other prominent problem is privacy concerns when applying machine learning algorithms, and as the general public is becoming more concerned about their privacy, more works are definitely desired towards privacy-preserving machine learning systems.
Motivated by this situation, this workshop solicits original contributions on the security and privacy problems of machine learning algorithms and systems, including adversarial learning, algorithm robustness analysis, privacy-preserving machine learning, etc. We hope this workshop can bring researchers together to exchange ideas on cutting-edge technologies and brainstorm solutions for urgent problems derived from practical applications.
TOPICS
Topics of interest include, but are not limited, to the following:
- Application of Machine Learning for Software Security
- Security Testing & Validation of Machine Learning Systems
- Adversarial Machine Learning
- Robustness Analysis of Machine Learning Algorithms
- Detection and Defense to Training Data set Poison attack (including backdoor attacks)
- Privacy-Preserving Machine Learning
- Watermarking of Machine Learning Algorithms and Systems
- Attack and defense of face recognition systems
- Attacks and defense of voice recognition and voice commanded systems
- Attacks and defense of machine learning algorithms in program analysis
- Malware identification and analysis
- Spam and phishing email detection
- Vulnerability analysis
SUBMISSION GUIDELINES
Authors are welcome to submit their papers in the following two forms:
-
Full papers that present relatively mature research results related to security issues of machine learning algorithms, systems, and applications. The paper could be an attack, defense, security analysis, surveys, etc. The submissions for this type must follow the original LNCS format (see LNCS format) with a page limit of 18 pages (including references) for the main part (reviewers are not required to read beyond this limit) and 20 pages in total. Note that the page limit for the camera-ready paper is set to a maximum of 20 pages (in LNCS format).
-
Short papers that describe ongoing work and bring some new insights and inspiring ideas related to security issues of machine learning algorithms, systems, and applications. Short papers will follow the same LNCS format as full paper (see LNCS format), but with a page limit of 9 pages (including references).
The submissions must be anonymous, with no author names, affiliations, acknowledgment, or obvious references. Once accepted, the papers will appear in the formal proceedings. Authors of accepted papers must guarantee that their papers will be presented at the conference and must make their papers available online. There will be the best paper award.
- Special Note to Springer LNCS Proceedings: Authors should consult Springer's authors guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. In addition, the corresponding author of each paper, acting on behalf of all of the authors of that paper, must complete and sign a Consent-to-Publish form, through which the copyright for their paper is transferred to Springer. The corresponding author signing the copyright form should match the corresponding author marked on the paper. Once the files have been sent to Springer, changes relating to the authorship of the papers cannot be made.
EasyChair System will be used for paper submission.
Submission Link
Submission deadline has passed.
Please submit your paper via Easychair: Easychair submission link.
BEST PAPER AWARD
Each workshop affiliated with ACNS 2023 will nominate the best paper candidates. Best workshop papers will be selected and awarded a 500 EUR prize sponsored by Springer.
INVITED SPEAKERS
Keynote by Prof. Masashi Sugiyama, the Director of RIKEN Center for Advanced Intelligence Project and Professor, The University of Tokyo.
There will be 1-2 invited speakers in the workshop.
WORKSHOP ORGANIZERS
| Name | Institution | Chair |
|---|---|---|
| Ezekiel Soremekun | Royal Holloway, University of London | Workshop Chair |
| Badr Souani | SnT, University of Luxembourg | Web Chair |
| Salah Ghamizi | SnT, University of Luxembourg | Publicity Chair |
PROGRAM COMMITTEE
| Name | Institution |
|---|---|
| Alexander Bartel | Umeå University |
| Apratim Bhattacharyya | Qualcomm AI Research |
| Ezekiel Soremekun | Royal Holloway, University of London |
| Martin Gubri | SnT, University of Luxembourg |
| Maxime Cordy | SnT, University of Luxembourg |
| Sakshi Udeshi | Lumeros AI |
| Salah Ghamizi | SnT, University of Luxembourg |
| Sudipta Chattopadhyay | Singapore University of Technology and Design |
| Wang Jingyi | Zhejiang University |
WORKSHOP REGISTRATION
Please Register Here.
Registration is free for students.
PROGRAM
| Time Table : 19th June, 2023 (Virtual) |
|---|
| JST (UTC+9) | UTC | Agenda | Chair | Details |
|---|---|---|---|---|
| 15:30 | 6:30 | Opening | Ezekiel Soremekun | |
| 15:45 | 6:45 | Invited Talk | Salah Ghamizi | Speaker Name: Prof. Masashi Sugiyama Affiliation: RIKEN Center for Advanced Intelligence Project Title: "Towards Trustworthy Machine Learning from Weakly Supervised, Noisy, and Biased Data" |
| 16:45 | 7:45 | Break | ||
| 17:00 | 8:00 | Paper (30 min each) | Ezekiel Soremekun | (1) Aldin Vehabovic, Hadi Zanddizari, Farooq Shaikh, Nasir Ghani, Morteza Safaei Pour, Elias Bou Harb and Jorge Crichigno. Federated Learning Approach for Distributed Ransomware Analysis (2) Mohammed M. Alani, Atefeh Mashatan and Ali Miri. Forensic Identification of Android Trojans Using Stacked Ensemble of Deep Neural Networks (3) Haibo Zhang, Zhihua Yao and Kouichi Sakurai. Eliminating Adversarial Perturbations Using Image-to-Image Translation Method |
| 18:30 | 9:30 | Closing | Ezekiel Soremekun |
CONTACT INFORMATION
For more information, please contact the organizer Ezekiel Soremekun