Several available DL frameworks allow researchers and practitioners to train models using their data and use them internally in their local business processes [5– 7]. In this scenario, privacy …
PoPETs Proceedings — SoK: Efficient Privacy-preserving Clustering
SoK: Efficient Privacy-preserving Clustering Authors: Aditya Hegde (IIIT-Bangalore), Helen Möllering (Technical University of Darmstadt), Thomas Schneider (Technical ...
In today’s world, machine learning (ML) algorithms are widely used to categorize and classify large amounts of data. Applications range from spam filtering over fraud detection, stock …
SoK: Privacy-Preserving Computation Techniques for Deep Learning
SoK: Privacy-Preserving Computation Techniques for Deep Learning Authors: José Cabrero-Holgueras (CERN/Universidad Carlos III de Madrid), Sergio Pastrana ...
The PoPETS double-blind peer-review process is similar to other top-tier computer security publications. The process includes initial review by the Editors-in-Chief for rules compliance …
To unify future research in this field, we developed a toolchain to process website privacy policies and pre-pare them for research purposes. The core part of this chain is a detector module for …
Abstract:Wedesignandimplementanefficient,secure, homomorphick-Nearest Neighbours determination al- gorithm,tobeusedforregressionorclassificationover privatedata ...
The first and third capabilities are motivated directly by shortcomings in the CA ecosystem as well as how the anonymity of Tor Browser is known to be attacked. The second capability assumes …
Wouter Lueks*, Seda Gürses, Michael Veale, Edouard Bugnion, Marcel Salathé, Kenneth G. Paterson, and Carmela Troncoso
2.1 Background on Digitalization in Agriculture Several benefits of digitalized agriculture are mentioned in previous research: First, it improves traceability. Re-tailers could offer their …