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Wissenschaftliche und technische Beiträge zu unserem Projekt

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Bin Liu, Antonis Michalas and Bogdan Warinschi. “Cryptographic Role-Based Access Control, Reconsidered”. Proceedings of the 16th International Conference on Provable and Practical Security (ProvSec’22), Nanjing, China, 11–12 November 2022.
R. Guanciale, N. Paladi and A. Vahidi, "SoK: Confidential Quartet - Comparison of Platforms for Virtualization-Based Confidential Computing," 2022 IEEE International Symposium on Secure and Private Execution Environment Design (SEED), Storrs, CT, USA, 2022, pp. 109-120, doi: 10.1109/SEED55351.2022.00017.
Alexandros Bakas, Eugene Frimpong and Antonis Michalas. “Symmetrical Disguise: Realizing Homomorphic Encryption Services from Symmetric Primitives”. Proceedings of the 18th EAI International Conference on Security and Privacy in Communication Networks (SecureComm’22), Kansas City, United States, October 17–19, 2022.
Alexandros Bakas, Antonis Michalas, Eugene Frimpong and Reyhaneh Rabbaninejad. “Feel the Quantum Functioning: Instantiating Generic Multi-Input Functional Encryption from Learning with Errors”. Proceedings of the 36th Annual WG 11.3 Conference on Data and Applications Security and Privacy (DBSec’22), Newark, NJ, USA, July 18–20, 2022.
Title: stoRNA: Stateless Transparent Proofs of Storage-time

Authors: Reyhaneh Rabaninejad, Behzad Abdolmaleki, Giulio Malavolta, Antonis Michalas and Amir Nabizadeh

Venue: Proceedings of the 28th European Symposium on Research in Computer Security (ESORICS 2023), Hague, the Netherlands, September 25–29, 2023.
Title: Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning

Authors: Tanveer Khan, Khoa Nguyen and Antonis Michalas

Venue: Proceedings of the 5th International Workshop on Health Data Management in the Era of AI (HeDAI'23), co-located with the 26th International Conference on Extending Database Technology, 28-31 March, 2023, Ioannina, Greece.

Han Wang, David Eklund, Alina Oprea, Shahid Raza - "FL4IoT: IoT Device Fingerprinting and Identification using Federated Learning", Published: 09 June 2023
Tanveer Khan, Antonis Michalas: Learning in the Dark: Privacy-Preserving Machine
Learning using Function Approximation
Tanveer Khan, Khoa Nguyen, Antonis Michalas: A More Secure Split: Enhancing the Security of Privacy-Preserving Split Learning
Tanveer Khan, Khoa Nguyen, Antonis Michalas and Alexandros Bakas: Love or Hate? Share or Split? Privacy-Preserving Training
Using Split Learning and Homomorphic Encryption
Khoa Nguyen, Tanveer Khan, Antonis Michalas: Split Without a Leak: Reducing Privacy Leakage
in Split Learning