A privacy preserving machine learning framework for medical image analysis using quantized fully connected neural networks with TFHE based inference. [PDF]
Selvakumar S, Senthilkumar B.
europepmc +1 more source
Synchronizing LLM-based semantic knowledge bases via secure federated fine-tuning in semantic communication. [PDF]
Li L +6 more
europepmc +1 more source
A privacy preserving medical data management framework using blockchain enabled encrypted role based access control. [PDF]
Taloba AI, Rayan A.
europepmc +1 more source
A privacy-preserving HLA imputation method with homomorphic encryption. [PDF]
Kim H, Hwang I, Song Y, Han B.
europepmc +1 more source
A multidimensional, efficient, and secure data query based on privacy preservation in vehicular ad hoc networks. [PDF]
Zhao X, Dong G.
europepmc +1 more source
Editorial: Theoretical advances and practical applications of spiking neural networks, volume II. [PDF]
Di Caterina G, Zhang M, Liu J.
europepmc +1 more source
Fully Homomorphic Encryption for Cyclotomic Prime Moduli
Geelen, Robin, Vercauteren, Frederik
openaire +3 more sources
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Parallelizing Fully Homomorphic Encryption
2014 International Symposium on Computer, Consumer and Control, 2014As cloud computing has grown increasingly prevalent, the privacy of data on the cloud becomes an issue. Encryption is an effective way to enforce data privacy. However most of existing encryption schemes require data to be decrypted for computations where data becomes vulnerable for data intrusion.
Ryan Hayward, Chia Chu Chiang
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Homomorphic encryption is a very useful tool with a number of attractive applications. However, the applications are limited by the fact that only one operation is possible (usually addition or multiplication in the plaintext space) to be able to manipulate the plaintext by using only the ciphertext. What would really be useful is to be able to utilize
Xun Yi, Russell Paulet, Elisa Bertino
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