Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Amos Treiber"'
Publikováno v:
Proceedings of the 21st Workshop on Privacy in the Electronic Society.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b632c0547403154d81fca286dd9c211
https://doi.org/10.1145/3559613.3563192
https://doi.org/10.1145/3559613.3563192
Publikováno v:
2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26be2e62d80e2a27cc56eeeca64e35c0
https://doi.org/10.1109/eurosp53844.2022.00014
https://doi.org/10.1109/eurosp53844.2022.00014
Publikováno v:
Speech Communication. 114:60-71
The usage of biometric recognition has become prevalent in various verification processes, ranging from unlocking mobile devices to verifying bank transactions. Automatic speaker verification (ASV) allows an individual to verify its identity towards
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60afd4bf2792029e5828b22c5b382d5a
https://doi.org/10.1016/j.specom.2019.09.004
https://doi.org/10.1016/j.specom.2019.09.004
Publikováno v:
PPMLP@CCS
Proceedings of the 2020 Workshop on Privacy-Preserving Machine Learning in Practice
Proceedings of the 2020 Workshop on Privacy-Preserving Machine Learning in Practice
The ubiquitous deployment of machine learning (ML) technologies has certainly improved many applications but also raised challenging privacy concerns, as sensitive client data is usually processed remotely at the discretion of a service provider. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84448dd4743eae9622b7ce327b90c7fa
https://doi.org/10.1145/3411501.3419417
https://doi.org/10.1145/3411501.3419417
Publikováno v:
24. European Conference on Artificial Intelligence (ECAI'20)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::0ed46c6adbb19df8149e2554fc296393
Autor:
Thomas Schneider, Petr Mizera, Nicholas Evans, Massimiliano Todisco, Andreas Nautsch, Jose Patino, Amos Treiber, Themos Stafylakis
Publikováno v:
INTERSPEECH
In many voice biometrics applications there is a requirement to preserve privacy, not least because of the recently enforced General Data Protection Regulation (GDPR). Though progress in bringing privacy preservation to voice biometrics is lagging be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f8d398368b1aebebda477cdfaf793cd
http://arxiv.org/abs/1907.03454
http://arxiv.org/abs/1907.03454
Autor:
Thomas Schneider, Amos Treiber
Privacy-preserving scalar product (PPSP) protocols are an important building block for secure computation tasks in various applications. Lu et al. (TPDS'13) introduced a PPSP protocol that does not rely on cryptographic assumptions and that is used i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45d39db081a3360a818bc1267cb2553a
http://arxiv.org/abs/1906.04862
http://arxiv.org/abs/1906.04862
Publikováno v:
WPES@CCS
Oblivious RAM is a cryptographic primitive that embodies one of the cornerstones of privacy-preserving technologies for database protection. While any Oblivious RAM (ORAM) construction offers access pattern hiding, there does not seem to be a constru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2787c2632c5d4751f3fb7919fc9a0ce8
https://doi.org/10.1145/3267323.3268963
https://doi.org/10.1145/3267323.3268963