Results 121 to 130 of about 1,042,584 (201)
Differential Privacy Preservation for Continuous Release of Real-Time Location Data. [PDF]
Entropy (Basel)Mao L, Xu Z.
europepmc +1 more source
Secure Data Aggregation Using Authentication and Authorization for Privacy Preservation in Wireless Sensor Networks. [PDF]
Sensors (Basel)Erskine SK.
europepmc +1 more source
End-to-end pseudonymization of fine-tuned clinical BERT models : Privacy preservation with maintained data utility. [PDF]
BMC Med Inform Decis MakVakili T, Henriksson A, Dalianis H.
europepmc +1 more source
Smart city energy efficient data privacy preservation protocol based on biometrics and fuzzy commitment scheme. [PDF]
Sci RepNyangaresi VO +8 more
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
SSRN Electronic Journal, 2023
A signal is privacy‐preserving with respect to a collection of privacy sets if the posterior probability assigned to every privacy set remains unchanged conditional on any signal realization. We characterize the privacy‐preserving signals for arbitrary state space and arbitrary privacy sets.
Strack, Philipp, Yang, Kai Hao
openaire +2 more sources
A signal is privacy‐preserving with respect to a collection of privacy sets if the posterior probability assigned to every privacy set remains unchanged conditional on any signal realization. We characterize the privacy‐preserving signals for arbitrary state space and arbitrary privacy sets.
Strack, Philipp, Yang, Kai Hao
openaire +2 more sources
Data Mining and Knowledge Discovery, 2007
We describe two algorithms, BiBoost (Bipartite Boosting) and MultBoost (Multiparty Boosting), that allow two or more participants to construct a boosting classifier without explicitly sharing their data sets. We analyze both the computational and the security aspects of the algorithms.
Gambs, Sebastien +2 more
openaire +2 more sources
We describe two algorithms, BiBoost (Bipartite Boosting) and MultBoost (Multiparty Boosting), that allow two or more participants to construct a boosting classifier without explicitly sharing their data sets. We analyze both the computational and the security aspects of the algorithms.
Gambs, Sebastien +2 more
openaire +2 more sources