ADSPP 2025 Workshop
The 18th KSEM 2025 Workshop on Advanced Data Security and Privacy Preservation in AI (ADSPP 2025)
In the rapidly advancing field of artificial intelligence (AI), the integration of sophisticated algorithms and vast datasets has revolutionized numerous industries, from healthcare and finance to smart cities and cybersecurity. The deployment of AI technologies relies heavily on the availability and utilization of large datasets, which often contain sensitive and personal information. As AI systems become more pervasive, the potential risks associated with data breaches, unauthorized access, and misuse of information escalate. Additionally, the rise of sophisticated cyber threats targeting AI models themselves—such as adversarial attacks, model inversion, and data poisoning—further complicates the landscape of data security and privacy. Regulatory frameworks like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) emphasize the necessity for robust data protection measures, making it imperative for AI systems to incorporate advanced security and privacy-preserving techniques.
Ensuring data security and privacy in AI is not merely a technical requirement but a fundamental ethical responsibility. Effective protection mechanisms foster trust among users and stakeholders, ensure compliance with legal standards, and mitigate the risks of financial loss and reputational damage due to data breaches. In the context of AI, safeguarding data integrity and confidentiality is essential for the reliable and ethical deployment of technologies such as large language models (LLMs), autonomous systems, and cognitive analytics. By focusing on advanced data security and privacy preservation, this workshop aims to promote the development of AI systems that are both innovative and secure, thereby supporting sustainable and ethical technological progress.
This workshop invites contributions that delve into innovative approaches, methodologies, and applications related to data security and privacy in AI. Topics of interest include, but are not limited to:
- Privacy-Preserving Machine Learning
- Data Encryption and Access Control
- AI Model Security
- Secure Knowledge Representation
- Privacy in Large Language Models (LLMs)
- Knowledge Graph Security
- Secure Data Sharing and Collaboration
- Anomaly Detection in Data Streams
- Automated Privacy Policy Generation
- Zero-Knowledge Proofs in AI Systems
- Secure Data Provenance and Lineage
- Privacy Risk Assessment Frameworks
- Secure Multi-Party Computation for AI
- Adaptive Privacy Mechanisms in Dynamic Environments
- Homomorphic Encryption for Real-Time AI
- Privacy Preservation in Edge AI Computing
- Secure Transfer Learning Techniques
- Differential Privacy in Reinforcement Learning
- Privacy-Preserving Data Synthesis and Augmentation
- Ethical AI Design for Privacy Protection
- Privacy-Enhanced Natural Language Processing
- Paper Submission Due: 04 March, 2025
- Notification of acceptance: 30 May, 2025
- Camera-ready copy: 15 June, 2025
- Conference date: 04-06 August, 2025
Papers will be submitted through EasyChair at the following link: https://easychair.org/conferences?conf=ksem2025 (choose ADSPP track)
General Chair
Zhitao Guan, North China Electric Power University, China
Chuan Zhang, Beijing Institute of Technology, China
Ying Zhang, North China Electric Power University, China
Yajie Wang, Beijing Institute of Technology, China, wangyajie0312@foxmail.com.
Qing Fan, North China Electric Power University, China, qingfancassie@163.com.
Xiangyun Tang, Minzu University of China, China, xiangyunt@muc.edu.cn.
Program Chairs
Jiawen Kang, Guangdong University of Technology, China
Tao Zhang, Beijing Jiaotong University, China
Publication Chair
Hongyang Du, University of Hong Kong, Hong Kong, China
Chuan Zhou, Minzu University of China, China
Workshop Chairs
Yijing Lin, Beijing University of Posts and Telecommunications, China
Yutong Gao, Minzu University of China, China
Xuan Liu , Minzu University of China, China
Publicity Chair
Jiacheng Wang, Nanyang Technological University, Singapore
Zheng Liu, Minzu University of China, China
