7 citations · 16 across the 11 of their papers we have counts for
7 papers · 1 filter
When Federated Learning meets Watermarking: A Comprehensive Overview of Techniques for Intellectual Property Protection
Mohammed Lansari, Reda Bellafqira, Katarzyna Kapusta +3
Federated Learning (FL) is a technique that allows multiple participants to collaboratively train a Deep Neural Network (DNN) without the need of centralizing their data. Among oth…
Revisiting Shared Data Protection Against Key Exposure
Katarzyna Kapusta, Gerard Memmi, Matthieu Rambaud
This paper puts a new light on secure data storage inside distributed systems. Specifically, it revisits computational secret sharing in a situation where the encryption key is exp…
PE-AONT: Partial Encryption combined with an All-or-Nothing Transform
Katarzyna Kapusta, Gerard Memmi
In this report, we introduce PE-AONT: a novel algorithm for fast and secure data fragmentation. Initial data are fragmented and only a selected subset of the fragments is encrypted…
A Fast Fragmentation Algorithm For Data Protection In a Multi-Cloud Environment
Katarzyna Kapusta, Gerard Memmi
Data fragmentation and dispersal over multiple clouds is a way of data protection against honest-but-curious storage or service providers. In this paper, we introduce a novel algor…
Data protection by means of fragmentation in various different distributed storage systems - a survey
Katarzyna Kapusta, Gerard Memmi
This paper analyzes various distributed storage systems that use data fragmentation and dispersal as a way of protection.Existing solutions have been organized into two categories:…
An Efficient Keyless Fragmentation Algorithm for Data Protection
Katarzyna Kapusta, Gerard Memmi, Hassan Noura
The family of Information Dispersal Algorithms is applied to distributed systems for secure and reliable storage and transmission. In comparison with perfect secret sharing it achi…