Preprints

Conference Papers

• POSEIDON: Privacy-Preserving Federated Neural Network Learning
  Sinem Sav, Apostolos Pyrgelis, Juan R. Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, and Jean-Pierre Hubaux
  Network and Distributed Systems Security Symposium (NDSS), 2021
  
• SIMARD: A Simulated Annealing Based RNA Design Algorithm with Quality Pre-Selection Strategies
  Sinem Sav, David Hampson, and Herbert H. Tsang
  IEEE Symposium Series on Computational Intelligence (SSCI), 2016
  
• Examining the Annealing Schedules for RNA Design Algorithm
  Halid Emre Erhan, Sinem Sav, Stas Kalashnikov, and Herbert H. Tsang
  IEEE Congress on Evolutionary Computation, July 24-29, 2016
  
• Investigation of Multi-Objective Optimization Criteria for RNA Design
  David Hampson, Sinem Sav, and Herbert H. Tsang
  IEEE Symposium Series on Computational Intelligence (SSCI), 2016
  

Journals

• Privacy-Preserving Federated Recurrent Neural Networks
  Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, and Jean-Pierre Hubaux
  Proceedings on Privacy Enhancing Technologies (PoPETS 2023)
  
  
• Privacy-Preserving Federated Neural Network Learning for Disease-Associated Cell Classification
  Sinem Sav, Jean-Philippe Bossuat, Juan R. Troncoso-Pastoriza, Manfred Claassen, and Jean-Pierre Hubaux
  Patterns, Volume 3, 2022
  [Poster]
  
• Scalable Privacy-Preserving Distributed Learning
  David Froelicher, Juan R. Troncoso-Pastoriza, Apostolos Pyrgelis, Sinem Sav, Joao Sa Sousa, Jean-Philippe Bossuat, and Jean-Pierre Hubaux
  Proceedings on Privacy Enhancing Technologies (PoPETS 2021)
  

Workshop Papers

• SlytHErin: An Agile Framework for Encrypted Deep Neural Network Inference
  Francesco Intoci*, Sinem Sav*, Apostolos Pyrgelis, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, and Jean-Pierre Hubaux
  Accepted at 5th Workshop on Cloud Security and Privacy (Cloud S&P 2023) co-located with ACNS.
  
  

Patents

• System and method for privacy-preserving distributed training of neural network models on distributed datasets
  Sinem Sav, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, David Froelicher, Joao André Gomes de Sá e Sousa, Jean-Philippe Bossuat, Jean-Pierre Hubaux
  2022
  
• System and method for privacy-preserving distributed training of machine learning models on distributed datasets
  David Froelicher, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, Sinem Sav, Joao André Gomes de Sá e Sousa, Jean-Pierre Hubaux, Jean-Philippe Bossuat
  2021