Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications
S. Sanaullah, H. Attaullah, T. Jungeblut, in: O.A. Omitaomu, A. Mostafavi, S. Randhawa, H. Niu (Eds.), Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI, ACM, New York, NY, USA, 2024, pp. 50–53.
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Konferenzbeitrag
| Veröffentlicht
| Englisch
Autor*in
Herausgeber*in
Omitaomu, Olufemi A.;
Mostafavi, Ali;
Randhawa, Sukanya;
Niu, Haoran
Erscheinungsjahr
Titel des Konferenzbandes
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI
Seite
50-53
Konferenz
SIGSPATIAL '24: The 32nd ACM International Conference on Advances in Geographic Information Systems
Konferenzort
Atlanta GA USA
Konferenzdatum
2024-10-29 – 2024-11-01
ISBN
FH-PUB-ID
Zitieren
Sanaullah, Sanaullah ; Attaullah, Hasina ; Jungeblut, Thorsten: Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications. In: Omitaomu, O. A. ; Mostafavi, A. ; Randhawa, S. ; Niu, H. (Hrsg.): Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI. New York, NY, USA : ACM, 2024, S. 50–53
Sanaullah S, Attaullah H, Jungeblut T. Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications. In: Omitaomu OA, Mostafavi A, Randhawa S, Niu H, eds. Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI. New York, NY, USA: ACM; 2024:50-53. doi:10.1145/3681780.3697244
Sanaullah, S., Attaullah, H., & Jungeblut, T. (2024). Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications. In O. A. Omitaomu, A. Mostafavi, S. Randhawa, & H. Niu (Eds.), Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI (pp. 50–53). New York, NY, USA: ACM. https://doi.org/10.1145/3681780.3697244
@inproceedings{Sanaullah_Attaullah_Jungeblut_2024, place={New York, NY, USA}, title={Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications}, DOI={10.1145/3681780.3697244}, booktitle={Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI}, publisher={ACM}, author={Sanaullah, Sanaullah and Attaullah, Hasina and Jungeblut, Thorsten}, editor={Omitaomu, Olufemi A. and Mostafavi, Ali and Randhawa, Sukanya and Niu, HaoranEditors}, year={2024}, pages={50–53} }
Sanaullah, Sanaullah, Hasina Attaullah, and Thorsten Jungeblut. “Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications.” In Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI, edited by Olufemi A. Omitaomu, Ali Mostafavi, Sukanya Randhawa, and Haoran Niu, 50–53. New York, NY, USA: ACM, 2024. https://doi.org/10.1145/3681780.3697244.
S. Sanaullah, H. Attaullah, and T. Jungeblut, “Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications,” in Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI, Atlanta GA USA, 2024, pp. 50–53.
Sanaullah, Sanaullah, et al. “Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications.” Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI, edited by Olufemi A. Omitaomu et al., ACM, 2024, pp. 50–53, doi:10.1145/3681780.3697244.
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