58 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Virginia TechUS9 papers
- University of Maryland, College ParkUS4 papers
- Arizona State UniversityUS2 papers
- University of MiamiUS2 papers
- University of South FloridaUS2 papers
- Centre National de la Recherche ScientifiqueFR1 paper
- École & Observatoire des Sciences de la TerreFR1 paper
- Georgia Institute of TechnologyUS1 paper
- ObjectVideo (United States)US1 paper
- Old Dominion UniversityUS1 paper
- ShanghaiTech UniversityCN1 paper
- Syracuse UniversityUS1 paper
11 papers · 1 filter
Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing
Yi Shi, Yalin E. Sagduyu
Network slicing manages network resources as virtual resource blocks (RBs) for the 5G Radio Access Network (RAN). Each communication request comes with quality of experience (QoE)…
Adversarial Machine Learning for 5G Communications Security
Yalin E. Sagduyu, Tugba Erpek, Yi Shi
Machine learning provides automated means to capture complex dynamics of wireless spectrum and support better understanding of spectrum resources and their efficient utilization. A…
Reinforcement Learning for Dynamic Resource Optimization in 5G Radio Access Network Slicing
Yi Shi, Yalin E. Sagduyu, Tugba Erpek
The paper presents a reinforcement learning solution to dynamic resource allocation for 5G radio access network slicing. Available communication resources (frequency-time blocks an…
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…
Deep Learning for Wireless Communications
Tugba Erpek, Timothy J. O'Shea, Yalin E. Sagduyu +2
Existing communication systems exhibit inherent limitations in translating theory to practice when handling the complexity of optimization for emerging wireless applications with h…
Coherent Communications in Self-Organizing Networks with Distributed Beamforming
Yi Shi, Yalin E. Sagduyu
Coherent communications aim to support higher data rates and extended connectivity at lower power consumption compared with traditional point-to-point transmissions. The typical se…
Adversarial Deep Learning for Over-the-Air Spectrum Poisoning Attacks
Yalin E. Sagduyu, Yi Shi, Tugba Erpek
An adversarial deep learning approach is presented to launch over-the-air spectrum poisoning attacks. A transmitter applies deep learning on its spectrum sensing results to predict…
DeepWiFi: Cognitive WiFi with Deep Learning
Kemal Davaslioglu, Sohraab Soltani, Tugba Erpek +1
We present the DeepWiFi protocol, which hardens the baseline WiFi (IEEE 802.11ac) with deep learning and sustains high throughput by mitigating out-of-network interference. DeepWiF…
Trojan Attacks on Wireless Signal Classification with Adversarial Machine Learning
Kemal Davaslioglu, Yalin E. Sagduyu
We present a Trojan (backdoor or trapdoor) attack that targets deep learning applications in wireless communications. A deep learning classifier is considered to classify wireless…
When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing
Zhengping Luo, Shangqing Zhao, Zhuo Lu +2
Defense strategies have been well studied to combat Byzantine attacks that aim to disrupt cooperative spectrum sensing by sending falsified versions of spectrum sensing data to a f…
Deep Learning for Launching and Mitigating Wireless Jamming Attacks
Tugba Erpek, Yalin E. Sagduyu, Yi Shi
An adversarial machine learning approach is introduced to launch jamming attacks on wireless communications and a defense strategy is presented. A cognitive transmitter uses a pre-…