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pro vyhledávání: '"Kapusta, Katarzyna"'
Autor:
Lansari, Mohammed, Bellafqira, Reda, Kapusta, Katarzyna, Thouvenot, Vincent, Bettan, Olivier, Coatrieux, Gouenou
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 other advantages, it comes with privacy-preserving properties making it a
Externí odkaz:
http://arxiv.org/abs/2308.03573
Autor:
Winiarz, Piotr, Sroczyk, Ewa A., Brzoza-Kos, Agnieszka, Czaja, Paweł, Kapusta, Katarzyna, Świerczek, Konrad
Publikováno v:
In Acta Materialia 15 September 2024 277
Akademický článek
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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 exposed to an attacker. It comes with several contributions: First, it de
Externí odkaz:
http://arxiv.org/abs/1901.08083
In this work, we analyze the advantages of multi-hop data fragmentation in unattended wireless sensor networks (UWSN) and propose a lightweight protocol to achieve it. UWSN has recently become an important aspect in various areas of sensor networks w
Externí odkaz:
http://arxiv.org/abs/1901.05831
Autor:
Kapusta, Katarzyna, Memmi, Gerard
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. Further, fragments are transformed using a variation of an all-or-no
Externí odkaz:
http://arxiv.org/abs/1811.09144
Autor:
Kapusta, Katarzyna, Memmi, Gerard
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 algorithm for data fragmentation that is particularly well adapted to be us
Externí odkaz:
http://arxiv.org/abs/1804.01886
Autor:
Kapusta, Katarzyna, Memmi, Gerard
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: bitwise and structurewise. Systems from the bitwise category are oper
Externí odkaz:
http://arxiv.org/abs/1706.05960
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 achieves a significantly smaller memory overhead and better performance, b
Externí odkaz:
http://arxiv.org/abs/1705.09872
Hardening data protection using multiple methods rather than 'just' encryption is of paramount importance when considering continuous and powerful attacks in order to observe, steal, alter, or even destroy private and confidential information.Our pur
Externí odkaz:
http://arxiv.org/abs/1512.02951