Detecting Adversarial Attacks in the Context of Bayesian Networks

Autor: Marco Valtorta, Emad Alsuwat, John R. Rose, Csilla Farkas, Hatim Alsuwat

Publikováno v: Lecture Notes in Computer Science
33th IFIP Annual Conference on Data and Applications Security and Privacy (DBSec)
33th IFIP Annual Conference on Data and Applications Security and Privacy (DBSec), Jul 2019, Charleston, SC, United States. pp.3-22, ⟨10.1007/978-3-030-22479-0_1⟩
Data and Applications Security and Privacy XXXIII ISBN: 9783030224783
DBSec

Part 1: Attacks; International audience; In this research, we study data poisoning attacks against Bayesian network structure learning algorithms. We propose to use the distance between Bayesian network models and the value of data conflict to detect

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f6a070ee75b86006826bca7f5252659
https://hal.inria.fr/hal-02384585/document