Privacy-Preserving Techniques for Social Network Analysis

  • André L. C. Mendonça Universidade Federal do Ceará (UFC)
  • Felipe T. Brito Universidade Federal do Ceará (UFC)
  • Javam C. Machado Universidade Federal do Ceará (UFC)

Resumo


With the increasing concerns over data privacy, preserving the privacy of individuals in social network analysis has become crucial. This tutorial provides a comprehensive overview of methods and techniques to protect individual privacy while conducting social network analysis. We perform a deep analysis of differential privacy, which is a rigorous mathematical framework to protect individual privacy while enabling accurate analysis of network structure and characteristics. Additionally, this tutorial explores a variety of examples and case studies to demonstrate the application of these techniques in practical scenarios.
Palavras-chave: Differential Privacy, Social Network Analysis

Referências

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Publicado
25/09/2023
MENDONÇA, André L. C.; BRITO, Felipe T.; MACHADO, Javam C.. Privacy-Preserving Techniques for Social Network Analysis. In: TUTORIAIS - SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 38. , 2023, Belo Horizonte/MG. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 174-178. DOI: https://doi.org/10.5753/sbbd_estendido.2023.25632.