Privacy-preserving AI for future networks

Author:

Perino Diego1,Katevas Kleomenis1,Lutu Andra1,Marin Eduard1,Kourtellis Nicolas1

Affiliation:

1. Telefonica Research, Spain

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Reference6 articles.

1. Two Decades of AI4NETS - AI/ML for Data Networks: Challenges & Research Directions

2. Kattadige , C. , Raman , A. , Thilakarathna , K. , Lutu , A. , Perino , D. 360 NorVic : 360-degree video classification from mobile encrypted video traffic . In Proceedings of ACM NOSSDAV , 2021 . Kattadige, C., Raman, A., Thilakarathna, K., Lutu, A., Perino, D. 360NorVic: 360-degree video classification from mobile encrypted video traffic. In Proceedings of ACM NOSSDAV, 2021.

3. FLaaS

4. Mo , F. , Haddadi , H. , Katevas , K. , Marin , E. , Perino , D. and Kourtellis , N . Privacy-preserving federated learning with TEEs . In Proceedings of ACM MobiSys , 2021 (best paper). Mo, F., Haddadi, H., Katevas, K., Marin, E., Perino, D. and Kourtellis, N. Privacy-preserving federated learning with TEEs. In Proceedings of ACM MobiSys, 2021 (best paper).

5. Experience

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