10 citations · 25 across the 10 of their papers we have counts for
12 papers
Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks
Yi Shi, Yalin E. Sagduyu, Tugba Erpek
NextG networks are intended to provide the flexibility of sharing the spectrum with incumbent users and support various spectrum monitoring tasks such as anomaly detection, fault d…
Jamming Attacks on Federated Learning in Wireless Networks
Yi Shi, Yalin E. Sagduyu
Federated learning (FL) offers a decentralized learning environment so that a group of clients can collaborate to train a global model at the server, while keeping their training d…
Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications
Brian Kim, Yi Shi, Yalin E. Sagduyu +2
We consider adversarial machine learning based attacks on power allocation where the base station (BS) allocates its transmit power to multiple orthogonal subcarriers by using a de…
Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning
Yi Shi, Yalin E. Sagduyu
An over-the-air membership inference attack (MIA) is presented to leak private information from a wireless signal classifier. Machine learning (ML) provides powerful means to class…
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…
QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning
Nof Abuzainab, Tugba Erpek, Kemal Davaslioglu +8
The problem of quality of service (QoS) and jamming-aware communications is considered in an adversarial wireless network subject to external eavesdropping and jamming attacks. To…