@inproceedings{fc62a99b15d44e4fa9665fb9567f7103,
title = "Adversarial attacks on cognitive self-organizing networks: The challenge and the way forward",
abstract = "Future communications and data networks are expected to be largely cognitive self-organizing networks (CSON). Such networks will have the essential property of cognitive self-organization, which can be achieved using machine learning techniques (e.g., deep learning). Despite the potential of these techniques, these techniques in their current form are vulnerable to adversarial attacks that can cause cascaded damages with detrimental consequences for the whole network. In this paper, we explore the effect of adversarial attacks on CSON. Our experiments highlight the level of threat that CSON have to deal with in order to meet the challenges of next-generation networks and point out promising directions for future work.",
author = "Muhammad Usama and Junaid Qadir and Ala Al-Fuqaha",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 43rd Annual IEEE Conference on Local Computer Networks, LCN Workshops 2018 ; Conference date: 01-10-2018 Through 04-10-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/LCNW.2018.8628538",
language = "English",
series = "Proceedings of the 43rd Annual IEEE Conference on Local Computer Networks, LCN Workshops 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "90--97",
editor = "Soumaya Cherkaoui and Karl Andersson and Fadi Al-Turjman",
booktitle = "Proceedings of the 43rd Annual IEEE Conference on Local Computer Networks, LCN Workshops 2018",
address = "United States",
}