Results 51 to 60 of about 1,939,766 (365)
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
IEEE International Conference on Data Engineering, 2007 The k-anonymity privacy requirement for publishing microdata requires that each equivalence class (i.e., a set of records that are indistinguishable from each other with respect to certain "identifying" attributes) contains at least k records.
Ninghui Li +2 more
semanticscholar +1 more source
Privacy Preserving Data Mining
Advances in Information Security, 2015 Recent interest in data collection and monitoring using data mining for security and business-related applications has raised privacy. Privacy Preserving Data Mining (PPDM) techniques require data modification to disinfect them from sensitive information
J. Vaidya, Yu Zhu, C. Clifton
semanticscholar +1 more source
Certified Robustness to Adversarial Examples with Differential Privacy [PDF]
IEEE Symposium on Security and Privacy, 2018 Adversarial examples that fool machine learning models, particularly deep neural networks, have been a topic of intense research interest, with attacks and defenses being developed in a tight back-and-forth.
Mathias Lécuyer +4 more
semanticscholar +1 more source
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
Doppelganger Obfuscation — Exploring theDefensive and Offensive Aspects of Hardware Camouflaging
Transactions on Cryptographic Hardware and Embedded Systems, 2020 Hardware obfuscation is widely used in practice to counteract reverse engineering. In recent years, low-level obfuscation via camouflaged gates has been increasingly discussed in the scientific community and industry.
Max Hoffmann, Christof Paar
doaj +3 more sources
IEEE Access, 2017 With the advent of the Internet of Things, lightweight devices necessitate secure and cost-efficient key storage. Since traditional secure key storage is expensive, novel solutions have been developed based on the idea of deriving the key from noisy ...
Christopher Huth +4 more
doaj +1 more source
, 2013 Privacy is a Janus-faced value. It enables us to shut the world out, but the forms it takes and the extent to which it is protected are fundamentally public matters. Not surprisingly, then, privacy and its protection are the object of some of our most intractable conflicts over the proper role of the state and the rights and duties of individuals. This
openaire +4 more sources
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds [PDF]
, 2016 "Concentrated differential privacy" was recently introduced by Dwork and Rothblum as a relaxation of differential privacy, which permits sharper analyses of many privacy-preserving computations.
A Beimel +7 more
core +2 more sources
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response [PDF]
Conference on Computer and Communications Security, 2014 Randomized Aggregatable Privacy-Preserving Ordinal Response, or RAPPOR, is a technology for crowdsourcing statistics from end-user client software, anonymously, with strong privacy guarantees.
Ú. Erlingsson, A. Korolova, Vasyl Pihur
semanticscholar +1 more source
The Economics of Privacy [PDF]
Journal of Economic Literature, 2015 This article summarizes and draws connections among diverse streams of theoretical and empirical research on the economics of privacy. We focus on the economic value and consequences of protecting and disclosing personal information, and on consumers' understanding and decisions regarding the trade-offs associated with the privacy and the sharing of ...
Alessandro Acquisti (3880474) +2 more
openaire +4 more sources