Results 31 to 40 of about 1,840,684 (372)
End-to-end privacy preserving deep learning on multi-institutional medical imaging
Nature Machine Intelligence, 2021 Using large, multi-national datasets for high-performance medical imaging AI systems requires innovation in privacy-preserving machine learning so models can train on sensitive data without requiring data transfer.
Georgios Kaissis +13 more
semanticscholar +1 more source
ZOCB and ZOTR: Tweakable Blockcipher Modes for Authenticated Encryption with Full Absorption
IACR Transactions on Symmetric Cryptology, 2019 We define ZOCB and ZOTR for nonce-based authenticated encryption with associated data, and analyze their provable security. These schemes use a tweakable blockcipher (TBC) as the underlying primitive, and fully utilize its input to process a plaintext ...
Zhenzhen Bao +2 more
doaj +1 more source
THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption [PDF]
Findings, 2022 As more and more pre-trained language models adopt on-cloud deployment, the privacy issues grow quickly, mainly for the exposure of plain-text user data (e.g., search history, medical record, bank account).
Tianyu Chen +8 more
semanticscholar +1 more source
Privacy Preserving Average Consensus [PDF]
IEEE Transactions on Automatic Control, 2014 Average consensus is a widely used algorithm for distributed computing and control, where all the agents in the network constantly communicate and update their states in order to achieve an agreement. This approach could result in an undesirable disclosure of information on the initial state of agent i to the other agents.
Mo, Yilin, Murray, Richard M.
openaire +3 more sources
Privacy-preserving Linear Programming [PDF]
, 2018 A Book ...
Hong, Yuan +3 more
openaire +3 more sources
Privacy-Preserving Facial Recognition Using Biometric-Capsules [PDF]
, 2020 Indiana University-Purdue University Indianapolis (IUPUI)In recent years, developers have used the proliferation of biometric sensors in smart devices, along with recent advances in deep learning, to implement an array of biometrics-based recognition ...
Phillips, Tyler S.
core +1 more source
Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning
Future Internet, 2021 Privacy protection has been an important concern with the great success of machine learning. In this paper, it proposes a multi-party privacy preserving machine learning framework, named PFMLP, based on partially homomorphic encryption and federated ...
H. Fang, Q. Qian
semanticscholar +1 more source
Boomerang Connectivity Table Revisited. Application to SKINNY and AES
IACR Transactions on Symmetric Cryptology, 2019 The boomerang attack is a variant of differential cryptanalysis which regards a block cipher E as the composition of two sub-ciphers, i.e., E = E1 o E0, and which constructs distinguishers for E with probability p2q2 by combining differential trails for ...
Ling Song, Xianrui Qin, Lei Hu
doaj +1 more source
Intrusion Detection Based on Privacy-Preserving Federated Learning for the Industrial IoT
IEEE Transactions on Industrial Informatics, 2023 Federated learning (FL) has attracted significant interest given its prominent advantages and applicability in many scenarios. However, it has been demonstrated that sharing updated gradients/weights during the training process can lead to privacy ...
Pedro Ruzafa-Alcazar +6 more
semanticscholar +1 more source
The Novel Location Privacy-Preserving CKD for Mobile Crowdsourcing Systems
IEEE Access, 2018 With the development of mobile devices, mobile crowdsourcing has become the research hotspot in mobile crowd sensing networks (MCSS). How to protect the location privacy of mobile user in location-based services is a key problem in MCSS.
Zhongyang Chi +3 more
doaj +1 more source