KSEM 2025 provides a forum for academic researchers and industry practitioners to present research advancements, exchange new ideas, and identify future directions in the fields of Large Language Models (LLMs), Artificial Intelligence (AI) security, knowledge science, data science, engineering, machine learning, management and so on. KSEM 2025 is a CCF Rank-C conference. Accepted papers would be published by Springer and submitted to the EI database. Excellent papers with extension will be recommended for special issuesin renowned journals.

We invite submissions from academia, government and industry to present novel research on all aspects of knowledge and AI. Topics of KSEM include but are not limited to the following areas:

• Large Language Models (LLMs)
• Artificial intelligence (AI) security 
• Information security
• Knowledge representation & reasoning
• Formal analysis of knowledge
• Knowledge complexity & metrics
• Privacy preservation techniques
• Uncertainty in knowledge
• Knowledge fusion for decision making
• Knowledge and cyber security
• Formal ontologies
• Belief propagation & aggregation
• Cognitive foundations of knowledge
• Integration of machine learning and knowledge representation
• Knowledge-driven learning
• Knowledge-based attack and defense
• Knowledge for cognitive robotics
• Knowledge for cognitive analytics
• Knowledge in complex systems
• Game-theoretical knowledge
• knowledge in multi-agent systems
• Knowledge modeling
• Knowledge acquisition
• Knowledge extraction from resources
• Knowledge discovery from databases
• Knowledge integration
• Knowledge-based software engineering
• Knowledge-based systems conceptual modeling in knowledge-based systems
• Semantic database systems
• Semantic web and knowledge
• Knowledge engineering applications
• Knowledge modeling for digital twins
• Knowledge-based system for Chatbot
• Knowledge-based system and Large Language Models (LLMs)
• Privacy preservation and Large Language Models (LLMs)
• Model security and Large Language Models (LLMs)
• Knowledge management best practices and applications
• Knowledge verification and validation
• Knowledge protection and attack detection
• Knowledge-based systems in cybersecurity
• Smart knowledge and resource optimization
• Knowledge dissemination
• Knowledge management systems
• Knowledge and data integration
• Knowledge adaptation
• Knowledge management and Large Language Models (LLMs)
• Model fairness and Large Language Models (LLMs)
• Knowledge graph storage and management
• Probabilistic knowledge graphs
• Knowledge graph construction
• Knowledge graph query
• Learning on knowledge graphs
• Knowledge graph embedding
• Knowledge graph completion
• Multi-modal knowledge graphs
• Knowledge graph applications
• Deep graph neural networks