Results 61 to 70 of about 7,877,596 (288)

Differential privacy: an information-theoretic approach to preserve privacy in datasets

, 2022
reservedIn large datasets, anonymization may be not enough to preserve privacy. In recent years to tackle privacy preservation in datasets, it has been proposed a mathematical approach called differential privacy, which is the topic of this thesis.
FABRIS, GIULIA
core  

Survey on differential privacy and its progress

Tongxin xuebao, 2017
With the arrival of the era of big data sharing,data privacy protection issues will be highlighted.Since its introduction in 2006,differential privacy technology has been widely researched in data mining and data publishing.In recent years,Google,Apple ...
Zhi-qiang GAO, Yu-tao WANG
doaj   +2 more sources

Comparative Evaluation of Hemodiafiltration, Hemoperfusion, and Standard Hemodialysis on Efficacy, Inflammatory Control, Dialysis Adequacy, and Safety in End‐Stage Renal Disease: A Prospective Observational Study

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo, Weisi Dai, Jie Mao, Mei Ye, Xingshan Lu, Xiaocui Zhang   +5 more
wiley   +1 more source

On robustness and local differential privacy

The Annals of Statistics, 2023
It is of soaring demand to develop statistical analysis tools that are robust against contamination as well as preserving individual data owners' privacy. In spite of the fact that both topics host a rich body of literature, to the best of our knowledge, we are the first to systematically study the connections between the optimality under Huber's ...
Li, Mengchu, Berrett, Thomas B., Yu, Yi
openaire   +2 more sources

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

Molecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur, Joel Rodrigues Vitória, Manuel Saiselet, Ligia Craciun, Denis Larsimont, Anne Lefort, Frédérick Libert, Carine Maenhaut, Sabine Costagliola, Maxime Tarabichi, Mirian Romitti, Vincent Detours   +11 more
wiley   +1 more source

Random Differential Privacy

, 2013
We propose a relaxed privacy definition called {\em random differential privacy} (RDP). Differential privacy requires that adding any new observation to a database will have small effect on the output of the data-release procedure.
Alessandro Rinaldo, Robert Hall, Larry Wasserman   +2 more
core   +1 more source

On the `Semantics' of Differential Privacy: A Bayesian Formulation [PDF]

, 2014
Differential privacy is a definition of "privacy'" for algorithms that analyze and publish information about statistical databases. It is often claimed that differential privacy provides guarantees against adversaries with arbitrary side information.
Smith, Adam, Kasiviswanathan, Shiva Prasad, Adam Smith, Shiva Prasad Kasivisiwanathan, Shiva P. Kasiviswanathan   +4 more
core   +2 more sources

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source

Edge Local Differential Privacy for Dynamic Graphs

, 2023
AbstractHuge amounts of data are generated and shared in social networks and other network topologies. This raises privacy concerns when such data is not protected from leaking sensitive or personal information. Network topologies are commonly modeled through static graphs.
Sudipta Paul 0008, Julián Salas, Vicenç Torra   +2 more
openaire   +4 more sources

Marginal Release Under Local Differential Privacy [PDF]

Proceedings of the 2018 International Conference on Management of Data, 2018
Many analysis and machine learning tasks require the availability of marginal statistics on multidimensional datasets while providing strong privacy guarantees for the data subjects. Applications for these statistics range from finding correlations in the data to fitting sophisticated prediction models. In this paper, we provide a set of algorithms for
Graham Cormode, Tejas Kulkarni, Divesh Srivastava   +2 more
openaire   +4 more sources