Scope
We are excited to announce VAAL 2025 — the 7th Workshop on Vulnerability Analysis and Adversarial Learning! This workshop centers on the exploration of vulnerabilities in information systems, with a particular emphasis on security flaws in intelligent and AI-driven systems. We also focus on the real-world exploitation of these vulnerabilities, covering both offensive and defensive strategies that target AI algorithms, models, and systems. This year, VAAL 2025 will feature a special theme on vulnerability analysis and security challenges in Generative AI (GenAI) systems.
Traditionally, system vulnerabilities have stemmed from insecure software design, unsafe programming practices, and flawed system implementations. However, the rapid advancement of intelligent systems has introduced a new frontier of security concerns—vulnerabilities intrinsic to machine learning algorithms and AI models. Addressing these issues requires not only innovative defensive strategies but also opens up exciting opportunities for groundbreaking research.
At the heart of this effort is Adversarial Learning, a rapidly evolving field that lies at the intersection of machine learning and cybersecurity. Adversarial learning investigates how machine learning models perform when subjected to carefully crafted attacks and develops robust defense mechanisms to ensure the security and resilience of AI systems.
With the increasing importance of vulnerability analysis and adversarial learning, VAAL 2025 aims to bring together academic researchers, industry professionals, and practitioners from diverse disciplines. The workshop will provide a vibrant forum to share insights, exchange experiences, and explore future directions in this critical and dynamic area.
We look forward to your participation in VAAL 2025!WORKSHOP AREAS
Topic interest include but not limited to:
- Vulnerability Analysis of Information Systems
- Theory and Methods for Vulnerability Analysis
- Modeling and Pattern Recognition of Vulnerability Mechanisms
- AI-Powered Approaches for Vulnerability Analysis
- Vulnerability Analysis of AI Algorithms, Models, and Systems
- Vulnerabilities and Security Issues in Generative AI Systems
PAPER SUBMISSION
All submissions should be written in English and submitted via our submission system. A paper submitted to VAAL 2025 must not be under review for any other conference or journal during the entire period that it is being considered for VAAL 2025, and must be substantially different from any previously published work.
Submissions are reviewed in a single-blind manner. Please note that all submissions must strictly adhere to the IEEE templates provided at http://dsc.pcl.ac.cn/2025/submission.html. The templates also serve as a guideline for formatting. In particular, all submissions must use either the LaTeX template or the MS Word template. Please follow the instructions below carefully to ensure that your submission can ultimately be included in the proceedings.
IMPORTANT DATES
ORGANIZATION
Workshop Chair
Zhi Wang, Nankai University, China
Hu Li, National Key Laboratory of Science and Technology on Information System Security, China
Program Committee
Xiang Wang, National University of Defense Technology
Xiang Zhu, National University of Defense Technology
Shujie Yang, Beijing University of Posts and Telecommunications, China
Zhou Zan, Beijing University of Posts and Telecommunications, China
Yuanzhang Li, Beijing Institute of Technology, China
Long Luo, University of Electronic Science and Technology of China
Wei Kong, Zhejiang University of Technology, China
Jianwen Tian, Singapore Management University
Taotao Gu, Tsinghua University, China
Xifeng Wang, National Key Laboratory of Science and Technology on Information System Security, China
