Data Security and LLM Safety in Smart Systems (DLS)

Co-located with IEEE MASS 2025 | October 6–8, 2025

Scope

As smart systems integrate generative AI with edge-cloud architectures, their security paradigms face unprecedented challenges. Data security and LLM safety are crucial for trustworthy smart infrastructure. Data security protects sensitive information throughout its lifecycle, while LLM safety ensures the reliability and ethical alignment of AI behaviors. These two are intertwined: compromised data integrity directly undermines model robustness, and unsafe LLM outputs can lead to data breaches in interconnected smart ecosystems. This is especially critical in mobile environments with dynamic connectivity, resource constraints, and device diversity. Traditional frameworks, developed for static systems, are inadequate to address these dynamic, resource-constrained scenarios. The limitation is increasingly evident in real-world incidents across healthcare, transportation, and smart manufacturing sectors.

This workshop aims to unify data protection and AI safety for next-generation smart systems. While the main conference covers broader mobile ad-hoc network security, we specifically focus on emerging threats arising from the fusion of generative AI and distributed intelligence. Topics will span novel threat models, architectural safeguards, and evaluation methodologies that jointly strengthen data flows and AI behaviors. The outcomes will deliver practical guidelines to help academia and industry harness LLMs' transformative potential while mitigating systemic risks in critical applications like smart healthcare, autonomous transportation, and industrial IoT.

Topics of Interest

We invite submissions on emerging challenges including but not limited to:

  • Detection for Data Integrity in Smart Environment
  • Federated Fine-Tuning with Data Provenance Tracking
  • Dynamic Access Control and Data Security in Heterogeneous AI Systems
  • Blockchain-enabled Decentralized AI Governance
  • Incentive-Aware Security Protocols in Decentralized AI
  • Byzantine-Robust Consensus for Mobile Model Sharing
  • Adversarial Attacks and Defenses in Mobile Networks
  • Model Extraction Attacks Against Edge-Deployed LLMs
  • Jailbreaking Risks in Autonomous Decision Systems
  • Security and Privacy of Distilled On-Device Models
  • Copyright Protection of LLMs for Smart Systems
  • Embodied AI Safety and LLM-enabled Cyber-Physical System Safety
  • Standardization of AI Accountability in Smart Infrastructures

Submission Guidelines

Format: All submissions should be written in English with a maximum length of 6 single-spaced, double-column pages using 10pt fonts on 8.5 in x 11 in paper, including all figures, tables, and references, in PDF format. Authors must use the Manuscript Templates for IEEE Conference Proceedings.

Review: Reviewing will be single-blind, i.e., authors can keep their names on their submitted workshop paper.

Submission Portal: Click here.

Authors are invited to submit original, unpublished workshop papers that are not currently under review elsewhere. Accepted workshop papers will be included in the conference proceeding published in the IEEE Xplore Digital Library. For all workshop papers, IEEE reserves the right to exclude the workshop paper from distribution after the conference if the workshop paper is not presented at the conference.

Important Dates

  • Submission Deadline: Monday, June 30, 2025
  • Acceptance Notification: Friday, July 31, 2025
  • Camera-ready Submission: Friday, August 7, 2025
  • Conference: October 6-8, 2025

Committees

General Chairs

  • Prof. Minghui Xu, Shandong University, China
  • Dr. Qin Hu, Georgia State University, USA

Publicity Chairs

  • Prof. Yue Zhang, Shandong University, China
  • Dr. Qinhong Jiang, The Hong Kong Polytechnic University, China

TPC Chair

  • Dr. Shan Wang, The Hong Kong Polytechnic University, China

Web Chair

  • Yueyan Dong, Shandong University, China

Program Committee

  • Akshita Maradapu Vera Venkata Sai, Towson University, USA
  • Chonghe Zhao, Nanyang Technological University, Singapore
  • Christopher Ellis, Ohio State University, USA
  • Chunchi Liu, Huawei Technologies, China
  • Kun Li, Shandong University, China
  • Mario Michael Kubek, Georgia State University, USA
  • Qi Luo, Hong Kong University of Science and Technology, China
  • Ruochen Zhou, The Hong Kong University of Science and Technology, China
  • Vishal Karande, Google, USA
  • Xiaodong Qi, The Hong Kong Polytechnic University, China
  • Xiaoli Zhang, University of Science and Technology, China
  • Xiaoqian (Tiffany) Zhang, University of Nebraska Omaha, USA
  • Yan Long, The University of Virginia, USA
  • Yasra Chandio, University of Massachusetts Amherst, USA
  • Yongshun Xu, Samsung Neurologica Corporation, USA
  • Youming Tao, TU Berlin, Germany