Results 81 to 90 of about 164,354 (261)

Local Differential Privacy: a tutorial

, 2019
In the past decade analysis of big data has proven to be extremely valuable in many contexts. Local Differential Privacy (LDP) is a state-of-the-art approach which allows statistical computations while protecting each individual user's privacy. Unlike Differential Privacy no trust in a central authority is necessary as noise is added to user inputs ...
openaire   +3 more sources

Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications

Advanced Functional Materials, EarlyView.
Quantum emitters in hexagonal boron nitride have emerged as a promising candidate for quantum information science. This review examines the fundamentals of these quantum emitters, including their level structures, defect engineering, and their possible chemical structures.
Thi Ngoc Anh Mai, Md Shakhawath Hossain, Nhat Minh Nguyen, Yongliang Chen, Chaohao Chen, Xiaoxue Xu, Quang Thang Trinh, Toan Dinh, Toan Trong Tran   +8 more
wiley   +1 more source

Adaptive personalized privacy-preserving data collection scheme with local differential privacy

Journal of King Saud University: Computer and Information Sciences
Local differential privacy (LDP) is a state-of-the-art privacy notion that enables terminal participants to share their private data safely while controlling the privacy disclosure at the source.
Haina Song, Hua Shen, Nan Zhao, Zhangqing He, Wei Xiong, Minghu Wu, Mingwu Zhang   +6 more
doaj   +1 more source

A Bespoke Programmable Interpenetrating Elastomer Network Composite Laryngeal Stent for Expedited Paediatric Laryngotracheal Reconstruction

Advanced Functional Materials, EarlyView.
A programmable interpenetrating double‐network architecture, created via 3D‐TIPS printing and resin infusion, synergistically combines thermoplastic and thermosetting elastomers to balance structural rigidity and surface softness—crucial for paediatric laryngeal stents.
Elizabeth F. Maughan, Lei Wu, Dong Zhang, Linxiao Wu, Graca Ferreira Vaz Pinto Mendes, Wanqiao J. Tu, Heping Ma, Toby J. Proctor, Colin R. Butler, Thomas Kjærgaard, Mark W. Lowdell, Martin A. Birchall, Robert E. Hynds, Richard Hewitt, Wenhui Song   +14 more
wiley   +1 more source

Efficiency in local differential privacy

The Annals of Statistics
We develop a theory of asymptotic efficiency in regular parametric models when data confidentiality is ensured by local differential privacy (LDP). Even though efficient parameter estimation is a classical and well-studied problem in mathematical statistics, it leads to several non-trivial obstacles that need to be tackled when dealing with the LDP ...
openaire   +3 more sources

The Realization of Multidirectional, Free‐Standing 3D Plasmonic Nanostructures via 3D Nanoprinting: A Case Study of Fractal Antennas

Advanced Functional Materials, EarlyView.
Free‐standing plasmonic gold‐based fractal antennas are fabricated by 3D nanoprinting, employing focused electron beam induced deposition and an optimized purification method to remove carbon while conserving structural fidelity. Simulation and experiment show broadband plasmonic activity, including customizable polarizability, thereby paving the way ...
Verena Reisecker, Robert Winkler, Ulrich Hohenester, Evelin Fisslthaler, Daniel Knez, Gerald Kothleitner, Georg Haberfehlner   +6 more
wiley   +1 more source

Sequential Data Collection Method with Condensed Local Differential Privacy

Shuju Caiji Yu Chuli
Condensed local differential privacy is a metric‑based relaxation of local differential privacy with better utility and flexibility than local differential privacy.
JIN Yan, ZHU Youwen, WU Qihui
doaj   +1 more source

Region‐to‐Region Unidirectional Connection In Vitro Brain Model for Studying Directional Propagation of Neuropathologies

Advanced Functional Materials, EarlyView.
A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang, Hui‐Wen Liu, Hyogeun Shin, Hyun Wook Kang, Minjin Kang, Jongbaeg Kim, Il‐Joo Cho, Nakwon Choi, Seok Chung, Hong Nam Kim   +9 more
wiley   +1 more source

Research on federated learning approach based on local differential privacy

Tongxin xuebao, 2022
As a type of collaborative machine learning framework, federated learning is capable of preserving private data from participants while training the data into useful models.Nevertheless, from a viewpoint of information theory, it is still vulnerable for ...
Haiyan KANG, Yuanrui JI
doaj   +2 more sources

Hierarchical Local Differential Privacy

Journal of Information Processing, 2023
Tomoaki Mimoto, Takashi Matsunaka, Hiroyuki Yokoyama, Toru Nakamura, Takamasa Isohara   +4 more
openaire   +1 more source