LAMPS '25: ACM CCS Workshop on Large AI Systems and Models with Privacy and Security Analysis

Kwok-Yan Lam; Xiaoning Liu; Derui Wang; Bo Li; Wenyuan Xu; Jieshan Chen; Minhui Xue; Xingliang Yuan; Guangdong Bai; Shuo Wang

doi:10.1145/3719027.3767670

Abstract

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. © 2025 Copyright held by the owner/author(s).

Original language	English
Pages (from-to)	4914-4915
Number of pages	2
Journal	Proceedings of the ACM SIGSAC Conference on Computer and Communications Security
Volume	CCS '25
Online published	22 Nov 2025
DOIs	https://doi.org/10.1145/3719027.3767670
Publication status	Published - 2025
Externally published	Yes
Event	32nd ACM SIGSAC Conference on Computer and Communications Security (CCS 2025) - Taipei, Taiwan, China Duration: 13 Oct 2025 → 17 Oct 2025

Research Keywords

AI systems and models
Critical infrastructure
Privacy
Security

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Cite this

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title = "LAMPS '25: ACM CCS Workshop on Large AI Systems and Models with Privacy and Security Analysis",

abstract = "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. {\textcopyright} 2025 Copyright held by the owner/author(s).",

keywords = "AI systems and models, Critical infrastructure, Privacy, Security",

author = "Kwok-Yan Lam and Xiaoning Liu and Derui Wang and Bo Li and Wenyuan Xu and Jieshan Chen and Minhui Xue and Xingliang Yuan and Guangdong Bai and Shuo Wang",

year = "2025",

doi = "10.1145/3719027.3767670",

language = "English",

volume = "CCS '25",

pages = "4914--4915",

note = "32nd ACM SIGSAC Conference on Computer and Communications Security (CCS 2025), CCS {\textquoteright}25 ; Conference date: 13-10-2025 Through 17-10-2025",

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TY - JOUR

T1 - LAMPS '25

T2 - 32nd ACM SIGSAC Conference on Computer and Communications Security (CCS 2025)

AU - Lam, Kwok-Yan

AU - Liu, Xiaoning

AU - Wang, Derui

AU - Li, Bo

AU - Xu, Wenyuan

AU - Chen, Jieshan

AU - Xue, Minhui

AU - Yuan, Xingliang

AU - Bai, Guangdong

AU - Wang, Shuo

PY - 2025

Y1 - 2025

N2 - 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. © 2025 Copyright held by the owner/author(s).

AB - 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. © 2025 Copyright held by the owner/author(s).

KW - AI systems and models

KW - Critical infrastructure

KW - Privacy

KW - Security

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U2 - 10.1145/3719027.3767670

DO - 10.1145/3719027.3767670

M3 - Meeting abstract

VL - CCS '25

SP - 4914

EP - 4915

JO - Proceedings of the ACM SIGSAC Conference on Computer and Communications Security

JF - Proceedings of the ACM SIGSAC Conference on Computer and Communications Security

Y2 - 13 October 2025 through 17 October 2025

ER -