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LAMPS '24: ACM CCS Workshop on Large AI Systems and Models with Privacy and Safety Analysis

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conference contribution
posted on 2025-01-03, 11:41 authored by Bo Li, Wenyuan Xu, Jieshan Chen, Yang ZhangYang Zhang, Minhui Xue, Shuo Wang, Guangdong Bai, Xingliang Yuan
With large AI systems and models (LAMs) playing an ever-growing role across diverse applications, their impact on the privacy and cybersecurity of critical infrastructure has become a pressing concern. The LAMPS workshop is dedicated to tackling these emerging challenges, promoting dialogue on cutting-edge developments and ethical issues in safeguarding LAMs within critical infrastructure contexts. Bringing together leading experts from around the world, this workshop will delve into the complex privacy and cybersecurity risks posed by LAMs in critical sectors. Attendees will explore innovative solutions, exchange best practices, and contribute to shaping the future research agenda, emphasizing the crucial balance between advancing AI technologies and securing critical digital and physical infrastructures.

History

Primary Research Area

  • Trustworthy Information Processing

Name of Conference

ACM Conference on Computer and Communications Security (CCS)

CISPA Affiliation

  • Yes

Page Range

4888-4889

Publisher

Association for Computing Machinery (ACM)

Open Access Type

  • Unknown

BibTeX

@conference{Li:Xu:Chen:Zhang:Xue:Wang:Bai:Yuan:2024, title = "LAMPS '24: ACM CCS Workshop on Large AI Systems and Models with Privacy and Safety Analysis", author = "Li, Bo" AND "Xu, Wenyuan" AND "Chen, Jieshan" AND "Zhang, Yang" AND "Xue, Minhui" AND "Wang, Shuo" AND "Bai, Guangdong" AND "Yuan, Xingliang", year = 2024, month = 12, pages = "4888--4889", publisher = "Association for Computing Machinery (ACM)", doi = "10.1145/3658644.3691335" }

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