When Wireless Security Meets Machine Learning: Motivation, Challenges,
and Research Directions

When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions

24 January 2020

William C. Headley

Papers citing "When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions"

10 / 10 papers shown

Title
Adversarial Attacks on LoRa Device Identification and Rogue Signal Detection with Deep Learning Y. Sagduyu T. Erpek 16 2 0 27 Dec 2023
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples Giovanni Apruzzese Rodion Vladimirov A.T. Tastemirova Pavel Laskov AAML 30 15 0 04 Jul 2022
Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications Brian Kim Yi Shi Y. Sagduyu T. Erpek S. Ulukus AAML 19 27 0 16 Sep 2021
Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning Yi Shi Y. Sagduyu 13 16 0 22 Jul 2021
Adversarial jamming attacks and defense strategies via adaptive deep reinforcement learning Feng Wang Chen Zhong M. C. Gursoy Senem Velipasalar AAML 13 8 0 12 Jul 2020
How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 17 29 0 15 May 2020
Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 15 111 0 11 May 2020
Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 46 68 0 05 Feb 2020
An Introduction to Deep Learning for the Physical Layer Tim O'Shea J. Hoydis AI4CE 89 2,171 0 02 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 264 3,110 0 04 Nov 2016