As Large AI Systems and Models (LAMs) become increasingly pivotal in a wide array of applications, their potential impact on the privacy and cybersecurity of critical infrastructure becomes a pressing concern. LAMPS is dedicated to addressing these unique challenges, fostering a dialogue on the latest advancements and ethical considerations in enhancing the privacy and cybersecurity of LAMs, particularly in the context of critical infrastructure protection.
LAMPS will bring together global experts to dissect the nuanced privacy and cybersecurity challenges posed by LAMs, especially in critical infrastructure sectors. This workshop will serve as a platform to unveil novel techniques, share best practices, and chart the course for future research, with a special emphasis on the delicate balance between advancing AI technologies and securing critical digital and physical systems.
Topics of interest include (but are not limited to):
Secure Large AI Systems and Models for Critical Infrastructure
Large AI Systems and Models' Privacy and Security Vulnerabilities
Data Anonymization and Synthetic Data
Human-Centric Large AI Systems and Models
Submitted papers must not substantially overlap with papers that have been published or simultaneously submitted to a journal or a conference with proceedings. Short submissions should be at most 4 pages in the ACM double-column format. Submissions should be at most 10 pages in the ACM double-column format, excluding well-marked appendices, and at most 12 pages in total. Systematization of knowledge (SoK) submissions could be at most 15 pages long, excluding well-marked appendices, and at most 17 pages. Submissions are not required to be anonymized.
Submission link: https://ccs24-lamps.hotcrp.com
Only PDF files will be accepted. Submissions not meeting these guidelines risk rejection without consideration of their merits. Authors of accepted papers must guarantee that one of the authors will register and present the paper at the workshop. Proceedings of the workshop will be available on a CD to the workshop attendees and will become part of the ACM Digital Library.
The archival papers will be included in the workshop proceedings. Due to time constraints, accepted papers will be selected for presentation as either talk or poster based on their review score and novelty. Nonetheless, all accepted papers should be considered as having equal importance.
Authors are responsible for obtaining appropriate publication clearances. Attendance and presentation by at least one author of each accepted paper at the workshop are mandatory for the paper to be included in the proceedings.
For any questions, please contact one of the workshop organizers at jason.xue@data61.csiro.au or wangshuosj@sjtu.edu.cn .
Chong | Xiang | Princeton University | United States of America |
Derui | Wang | CSIRO's Data61 | Australia |
Giovanni | Apruzzese | University of Liechtenstein | Liechtenstein |
Jamie | Hayes | Google Deepmind | United Kingdom |
Jinyuan | Jia | The Pennsylvania State University | United States of America |
Konrad | Rieck | TU Berlin | Germany |
Kristen | Moore | CSIRO's Data61 | Australia |
Mainack | Mondal | Indian Institute of Technology, Kharagpur | India |
Mathias | Humbert | University of Lausanne | Switzerland |
Minghong | Fang | Duke University | United States of America |
Peng | Gao | Virginia Tech | United States of America |
Pin-Yu | Chen | IBM Research | United States of America |
Sagar | Samtani | Indiana University | United States of America |
Sai Teja | Peddinti | United States of America | |
Shiqing | Ma | University of Massachusetts Amherst | United States of America |
Shuang | Hao | University of Texas at Dallas | United States of America |
Stjepan | Picek | Radboud University | Netherlands |
Tian | Dong | Shanghai Jiao Tong University | China |
Tianshuo | Cong | Tsinghua University | China |
Torsten | Krauß | University of Wuerzburg | Germany |
Varun | Chandrasekaran | University of Illinois Urbana-Champaign | United States of America |
Xiaoning | Du | Monash University | Australia |
Xinlei | He | The Hong Kong University of Science and Technology (Guangzhou) | China |
Yanjiao | Chen | Zhejiang University | China |
Yinzhi | Cao | Johns Hopkins University | United States of America |