The topics of this special session include but are not limited to the following topics:

  • Formulation of privacy, security, and fairness in evolutionary computation
  • New opportunities, challenges, and modeling brought by secure computing, outsourcing computing, federated computing to evolutionary computation
  • Privacy-preserving, secure, or fairness-aware distributed optimization/learning/computing
  • Privacy-preserving, secure, or fairness-aware solutions for federated data-driven optimization/learning/computing
  • Secure computing powered privacy-preserving evolutionary computation
  • Evolutionary computation as a service
  • Privacy-preserving optimization paradigms for optimization, such as centralized optimization, distributed optimization, and surrogate-assistant optimization
  • Privacy-preserving and fairness-aware multi-objective optimization
  • Applications of privacy-preserving, secure, or fairness-aware framework, algorithms, and methods of evolutionary computation
  • Benchmarks/performance metrics for privacy-preserving, secure, or fairness-aware evolutionary computation