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DNNs as Similitude Models for Sharing Big Data (Brief Announcement)
  • Philip DerbekoEmail author
  • Shlomi Dolev
  • Ehud Gudes
Conference paper
  • 553 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11527)

Abstract

The amount of data grows exponentially with time and the growth shows no signs of stopping. However, the data in itself is not useful until it can be processed, mined for information and queried. Thus, data sharing is a crucial component of modern computations. On the other hand, exposing the data might lead to serious privacy implications.

In our past research we suggested the use of similitude models, as compact models of data representation instead of the data itself. In this paper we suggest the use of deep neural networks (DNN) as data models to answer different types of queries. In addition, we discuss ownership of the DNN models and how to retain the ownership of the model after sharing it.

Keywords

Similitude model Big data Deep neural networks 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Ben-Gurion University of the NegevBeer-ShevaIsrael

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