68 citations · 278 across the 34 of their papers we have counts for
7 papers · 1 filter
Channel Effects on Surrogate Models of Adversarial Attacks against Wireless Signal Classifiers
Brian Kim, Yalin E. Sagduyu, Tugba Erpek +2
We consider a wireless communication system that consists of a background emitter, a transmitter, and an adversary. The transmitter is equipped with a deep neural network (DNN) cla…
Adversarial Attacks with Multiple Antennas Against Deep Learning-Based Modulation Classifiers
Brian Kim, Yalin E. Sagduyu, Tugba Erpek +2
We consider a wireless communication system, where a transmitter sends signals to a receiver with different modulation types while the receiver classifies the modulation types of t…
Generative Adversarial Network in the Air: Deep Adversarial Learning for Wireless Signal Spoofing
Yi Shi, Kemal Davaslioglu, Yalin E. Sagduyu
The spoofing attack is critical to bypass physical-layer signal authentication. This paper presents a deep learning-based spoofing attack to generate synthetic wireless signals tha…
Over-the-Air Membership Inference Attacks as Privacy Threats for Deep Learning-based Wireless Signal Classifiers
Yi Shi, Kemal Davaslioglu, Yalin E. Sagduyu
This paper presents how to leak private information from a wireless signal classifier by launching an over-the-air membership inference attack (MIA). As machine learning (ML) algor…
How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy
Brian Kim, Yalin E. Sagduyu, Kemal Davaslioglu +2
We consider the problem of hiding wireless communications from an eavesdropper that employs a deep learning (DL) classifier to detect whether any transmission of interest is presen…
Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers
Brian Kim, Yalin E. Sagduyu, Kemal Davaslioglu +2
This paper presents channel-aware adversarial attacks against deep learning-based wireless signal classifiers. There is a transmitter that transmits signals with different modulati…