Publications

5G, 6G and NextG Communications

U. Demir, K. Davaslioglu, Y. E. Sagduyu, T. Erpek, G. Anderson, and S. Kompella, "I-SCOUT: Integrated Sensing and Communications to Uncover Moving Targets in NextG Networks," to appear in IEEE Military Communications Conference (MILCOM), 2024.
Y. E. Sagduyu, T. Erpek, A. Yener, and S. Ulukus, “Low-Latency Task-Oriented Communications with Multi-Round, Multi-Task Deep Learning,” to appear in ACM Mobicom Workshop on Machine Learning for NextG Networks, 2024.
Y. E. Sagduyu, T. Erpek, A. Yener, and S. Ulukus, "Will 6G be Semantic Communications? Opportunities and Challenges from Task Oriented and Secure Communications to Integrated Sensing," IEEE Network, 2024.
Y. E. Sagduyu, T. Erpek, A. Yener, and S. Ulukus, "Joint Sensing and Semantic Communications with Multi-Task Deep Learning," IEEE Communications Magazine, 2024.
Y. E. Sagduyu, T. Erpek, S. Ulukus, and A. Yener, "Is Semantic Communications Secure? A Tale of Multi-Domain Adversarial Attacks," IEEE Communications Magazine, 2023
Y. E. Sagduyu, S. Ulukus, and A. Yener, "Task-Oriented Communications for NextG: End-to-End Deep Learning and AI Security Aspects," IEEE Wireless Communications, 2023.
Y. Shi, M. Costa, T. Erpek, and Y. E. Sagduyu, "Deep Reinforcement Learning for 5G Radio Access Network Slicing with Spectrum Coexistence," IEEE Networking Letters, 2023.
T. S. Cousik, V. K. Shah, J. H. Reed, T. Erpek, and Y. E. Sagduyu, "Deep Learning for Fast and Reliable Initial Access in AI-Driven 6G mmWave Networks," IEEE Transactions on Network Science and Engineering, 2022.
Y. Shi and Y. E. Sagduyu, "Sensing-Throughput Tradeoffs with Generative Adversarial Networks for NextG Spectrum Sharing," IEEE Military Communications Conference (MILCOM) Workshops, 2022.
K. Davaslioglu, T. Erpek, and Y. E. Sagduyu, "Autoencoder Communications with Optimized Interference Suppression for NextG RAN," IEEE Future Networks World Forum (FNWF), 2022.
Y. Shi and Y. E. Sagduyu, T. Erpek, and M. C. Gursoy, "Jamming Attacks on NextG Radio Access Network Slicing with Reinforcement Learning," IEEE Future Networks World Forum (FNWF), 2022.
F. Wang, M. C. Gursoy, S. Velipasalar, and Y. E. Sagduyu, "Robust Deep Reinforcement Learning Based Network Slicing Under Adversarial Jamming Attacks," IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2022.
Y. Shi, Y. E. Sagduyu, and T. Erpek, "Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks," SPIE Defense + Commercial Sensing (DCS) Conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 2022.
K. Davaslioglu, S. Boztas, M. C. Ertem, Y. E. Sagduyu, and E. Ayanoglu, "Self-Supervised RF Signal Representation Learning for NextG Signal Classification with Deep Learning," IEEE Wireless Communications Letters, 2022.
T. Erpek, Y. E. Sagduyu, A. Alkhateeb, and A. Yener, "Autoencoder-based Communications with Reconfigurable Intelligent Surfaces," IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2021.
Y. E. Sagduyu, T. Erpek, and Y. Shi, "Adversarial Machine Learning for 5G Communications Security," Game Theory and Machine Learning for Cyber Security, IEEE Press-Wiley, 2021.
N. Abuzainab, M. Alrabeiah, A. Alkhateeb, and Y. E. Sagduyu, "Deep Learning for THz Drones with Flying Intelligent Surfaces: Beam and Handoff Prediction," IEEE International Conference on Communications (ICC) Workshops, 2021.
Y. Shi and Y. E. Sagduyu, "Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing," IEEE International Conference on Communications (ICC) Workshops, 2021.
T. S. Cousik, V. K. Shah, J. H. Reed, T. Erpek, and Y. E. Sagduyu, "Fast Initial Access with Deep Learning for Beam Prediction in 5G mmWave Networks," IEEE Military Communications Conference (MILCOM), 2021.
B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, "How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy," Asilomar Conference on Signals, Systems, and Computers, 2020.
Y. Shi, T. Erpek, and Y. E. Sagduyu, "Reinforcement Learning for Dynamic Resource Optimization in 5G Radio Access Network Slicing,” IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2020.

Wireless Network, Information, and AI Security

K. Davaslioglu, S. Kompella, T. Erpek, and Y. E. Sagduyu, "Continual Deep Reinforcement Learning to Prevent Catastrophic Forgetting in Jamming Mitigation," to appear in IEEE Military Communications Conference (MILCOM), 2024.
M. Costa and Y. E. Sagduyu, "Timeliness in NextG Spectrum Sharing under Jamming Attacks with Deep Learning." IEEE Vehicular Technology Conference (VTC), 2024.
M. Costa and Y. E. Sagduyu, "Timely NextG Communications with Decoy Assistance against Deep Learning-based Jamming," IEEE International Conference on Communications Workshops (ICC Workshops), 2024.
Y. E. Sagduyu, T. Erpek, S. Ulukus, and A. Yener, "Vulnerabilities of Deep Learning-Driven Semantic Communications to Backdoor (Trojan) Attacks ," Conference on Information Sciences and Systems (CISS), 2023.
Y. E. Sagduyu and T. Erpek, "Adversarial Attacks on LoRa Device Identification and Rogue Signal Detection With Deep Learning," IEEE Military Communications (MILCOM), 2023.
Y. E. Sagduyu, T. Erpek, and Y. Shi, "Securing NextG Systems Against Poisoning Attacks on Federated Learning: A Game-Theoretic Solution," IEEE Military Communications (MILCOM), 2023.
M. Costa and Y. E. Sagduyu, "Timely and Covert Communications under Deep Learning-Based Eavesdropping and Jamming Effects," Journal of Communications and Networks, 2023.
Y. E. Sagduyu, Y. Shi, T. Erpek, W. Headley, B. Flowers, G. Stantchev, Z. Lu, and B. Jalaian, "Adversarial Machine Learning: A New Threat Paradigm for Next-Generation Wireless Communications," AI, Machine Learning and Deep Learning A Security Perspective, CRC Press, 2023.
Y. E. Sagduyu, Y. Shi, and T. Erpek, "Jamming Attacks on Decentralized Federated Learning in General Multi-Hop Wireless Networks," IEEE INFOCOM Wireless-Sec: 5G and Beyond Wireless Security Workshop, 2023.
Z. J. Luo, W. A. Pitera, S. Zhao, Z. Lu, and Y. E. Sagduyu, "How Can the Adversary Effectively Identify Cellular IoT Devices Using LSTM Networks?," ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) Workshop on Wireless Security and Machine Learning (WiseML), 2023.
Y. Shi and Y. E. Sagduyu, "How to Launch Jamming Attacks on Federated Learning in NextG Wireless Networks," IEEE Globecom Workshops (GC Wkshps): The Seventh IEEE Workshop on 5G and Beyond Wireless Security (7th IEEE Wireless-Sec), 2022.
Y. Shi, Y. E. Sagduyu, T. Erpek, M. C. Gursoy, "How to Attack and Defend NextG Radio Access Network Slicing with Reinforcement Learning," IEEE Open Journal of Vehicular Technology, 2022.
D. Adesina, C. C. Hsieh, Y. E. Sagduyu, and L. Qian, "Adversarial Machine Learning in Wireless Communications using RF Data: A Review," IEEE Communications Surveys & Tutorials, 2022.
Y. Shi and Y. E. Sagduyu, "Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning," IEEE Transactions on Mobile Computing, 2022.
B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, "Adversarial Machine Learning for NextG Covert Communications using Multiple Antennas," Entropy, 2022.
B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, "Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers," IEEE Transactions on Wireless Communications, 2022.
Z. Luo, S. Zhao, Z. Lu, J. Xu, and Y. E. Sagduyu, "When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing," IEEE Transactions on Mobile Computing, 2022.
T. Hou, T. Wang, Z. Lu, Y. Liu and Y. E. Sagduyu, "Undermining Deep Learning Based Channel Estimation via Adversarial Wireless Signal Fabrication," ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) Workshop on Wireless Security and Machine Learning (WiseML), 2022.
T. Hou, S. Bi, T. Wang, Z. Lu, Y. Liu, S. Misra, and Y. E. Sagduyu, "MUSTER: Subverting User Selection in MU-MIMO Networks," IEEE Conference on Computer Communications (INFOCOM), 2022.
B. Kim, T. Erpek, Y. E. Sagduyu, and S. Ulukus, "Covert Communications via Adversarial Machine Learning and Reconfigurable Intelligent Surfaces," IEEE Wireless Communications and Networking Conference (WCNC), 2022.
T. Hou, S. Bi, T. Wang, Z. Lu, Y. Liu, S. Misra, and Y. E. Sagduyu, "MUSTER: Subverting User Selection in MU-MIMO Networks," IEEE Conference on Computer Communications (INFOCOM), 2022.
B. Kim, T. Erpek, Y. E. Sagduyu, and S. Ulukus, "Covert Communications via Adversarial Machine Learning and Reconfigurable Intelligent Surfaces," IEEE Wireless Communications and Networking Conference (WCNC), 2022.
T. Hou, S. Bi, T. Wang, Z. Lu, Y. Liu, S. Misra, and Y. E. Sagduyu, "MUSTER: Subverting User Selection in MU-MIMO Networks," IEEE Conference on Computer Communications (INFOCOM), 2022.
B. Kim, T. Erpek, Y. E. Sagduyu, and S. Ulukus, "Covert Communications via Adversarial Machine Learning and Reconfigurable Intelligent Surfaces," IEEE Wireless Communications and Networking Conference (WCNC), 2022.
B. Kim, Y. Shi, Y. E. Sagduyu, T. Erpek, and S. Ulukus, "Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications," IEEE Global Communications Conference (GLOBECOM) Workshops, 2021.
T. Hou, T. Wang, Z. Lu, and Y. Liu, and Y. E. Sagduyu, "IoTGAN: GAN Powered Camouflage Against Machine Learning Based IoT Device Identification," IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2021.
Y. Shi, K. Davaslioglu, and Y. E. Sagduyu, "Generative Adversarial Network in the Air: Deep Adversarial Learning for Wireless Signal Spoofing," IEEE Transactions on Cognitive Communications and Networking, 2021.
Y. E. Sagduyu, Y. Shi, and T. Erpek, "Adversarial Deep Learning for Over-the-Air Spectrum Poisoning Attacks," IEEE Transactions on Mobile Computing, 2021.
B. Kim, Y. E. Sagduyu, T. Erpek, K. Davaslioglu, and S. Ulukus, "Channel Effects on Surrogate Models of Adversarial Attacks against Wireless Signal Classifiers," IEEE International Conference on Communications (ICC), 2021.
Z. Luo, S. Zhao, R. Duan, Z. Lu, Y. E. Sagduyu, and J. Xu, "Low-cost Influence-Limiting Defense against Adversarial Machine Learning Attacks in Cooperative Spectrum Sensing," ACM Workshop on Wireless Security and Machine Learning (WiseML), 2021.
B. Kim, Y. E. Sagduyu, T. Erpek, and S. Ulukus, "Adversarial Attacks on Deep Learning Based mmWave Beam Prediction in 5G and Beyond," IEEE Statistical Signal Processing Workshop, 2021.
B. Kim, Y. E. Sagduyu, T. Erpek, K. Davaslioglu, S. Ulukus, "Adversarial Attacks with Multiple Antennas Against Deep Learning-Based Modulation Classifiers," IEEE GLOBECOM Open Workshop on Machine Learning in Communications, 2020.
Y. Shi, K. Davaslioglu, and Y. E. Sagduyu, "Over-the-Air Membership Inference Attacks as Privacy Threats for Deep Learning-based Wireless Signal Classifiers," ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) Workshop on Wireless Security and Machine Learning (WiseML), 2020.
Z. Luo, S. Zhao, Z. Lu, Y. E. Sagduyu, and J. Xu, "Adversarial Machine Learning Based Partial-model Attack in IoT," ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) Workshop on Wireless Security and Machine Learning (WiseML), 2020.
B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, "Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels," Conference on Information Sciences and Systems (CISS), 2020.
K. Davaslioglu and Y. E. Sagduyu, "Trojan Attacks on Wireless Signal Classification with Adversarial Machine Learning," IEEE Workshop on Data-Driven Dynamic Spectrum Sharing of IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2019.
Y. Shi, K. Davaslioglu, and Y. E. Sagduyu, “Generative Adversarial Network for Wireless Signal Spoofing,” ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) Workshop on Wireless Security and Machine Learning (WiseML), 2019.
Y. E. Sagduyu, Y. Shi, and T. Erpek, "IoT Network Security from the Perspective of Adversarial Deep Learning," IEEE International Conference on Sensing, Communication and Networking (SECON) Workshop on Machine Learning for Communication and Networking in IoT, 2019.
T. Erpek, Y. E. Sagduyu, and Y. Shi, "Deep Learning for Launching and Mitigating Wireless Jamming Attacks," IEEE Transactions on Cognitive Communications and Networking, Mar. 2019.

Spectrum Situational Awareness and Advanced Networking

Y. E. Sagduyu, T. Erpek, A. Yener, and S. Ulukus, "Joint Sensing and Task-Oriented Communications with Image and Wireless Data Modalities for Dynamic Spectrum Access," IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Workshop on Signal Reuse for Spectrum Efficiency, 2024.
S. K. Kompella, K. Davaslioglu, Y. E. Sagduyu, and S. Kompella, “Augmenting Training Data With Vector-Quantized Variational Autoencoder for Classifying RF Signals,” to appear in IEEE Military Communication (MILCOM) Workshops, 2024.
Y. E. Sagduyu, T. Erpek, A. Yener, and S. Ulukus, "Multi-Receiver Task-Oriented Communications via Multi-Task Deep Learning," IEEE Future Networks World Forum, 2023.
Y. E. Sagduyu, S. Ulukus, and A. Yener, "Age of Information in Deep Learning-Driven Task-Oriented Communications," IEEE INFOCOM Age of Information (AOI) Workshop, 2023.
L. He, F. Hu, Z. Chu, J. Zhao, N. Abu Zainab, Y. E. Sagduyu, N. Thawdar, and S. Kumar. "Intelligent Terahertz Medium Access Control (MAC) for Highly Dynamic Airborne Networks." IEEE Transactions on Aerospace and Electronic Systems, 2022.
E. Ayanoglu, K. Davaslioglu, Y. E. Sagduyu, "Machine Learning in NextG Networks via Generative Adversarial Networks," IEEE Transactions on Cognitive Communications and Networking, 2022.
X. Wang, M. C. Gursoy, T. Erpek and Y. E. Sagduyu, "Learning-Based UAV Path Planning for Data Collection with Integrated Collision Avoidance," IEEE Internet of Things Journal, 2022.
Y. E. Sagduyu, "Adversarial Machine Learning and Defense Game for NextG Signal Classification with Deep Learning," IEEE Military Communications Conference (MILCOM) Workshops, 2022.
Y. E. Sagduyu, "Free-Rider Games for Federated Learning with Selfish Clients in NextG Wireless Networks," IEEE Conference on Communications and Network Security (CNS): Cyber Resilience Workshop, 2022.
K. Davaslioglu, S. Soltani, T. Erpek, and Y. E. Sagduyu, “DeepWiFi: Cognitive WiFi with Deep Learning,” IEEE Transactions on Mobile Computing, 2021.
Y. Shi and Y. E. Sagduyu, "Coherent Communications in Self-Organizing Networks with Distributed Beamforming," IEEE Transactions on Vehicular Technology,. 2020.
R. Theagarajan, B. Bhanu, T. Erpek, Y.-K. Hue, R. Schwieterman, K. Davaslioglu, Y. Shi, and Y. E. Sagduyu, "Integrating Deep learning-based Data driven and Model-based Approaches for Inverse Synthetic Aperture Radar Target Recognition," Optical Engineering Journal, 2020.
T. Erpek, T. O'Shea, Y. E. Sagduyu, Y. Shi, and T. C. Clancy, "Deep Learning for Wireless Communications" in Development and Analysis of Deep Learning Architectures, Springer, 2020.
Z. Lu, Y. E. Sagduyu, and Y. Shi, "Integrating Social Links into Wireless Networks: Modeling, Routing, Analysis and Evaluation," IEEE Transactions on Mobile Computing, 2019.
M. Costa and Y. E. Sagduyu, "Age of Information with Network Coding," Ad Hoc Networks Journal, 2019.
T. Erpek, Y. E. Sagduyu, Y. Shi, and S. Ponnaluri, "Network Control and Rate Optimization for Multiuser MIMO Communications," Ad Hoc Networks Journal, 2019.
Z. El Jamous, K. Davaslioglu, and Y. E. Sagduyu, "Deep Reinforcement Learning for Power Control in Next-Generation WiFi Network Systems," IEEE Military Communications Conference (MILCOM), 2022.
K. Davaslioglu, T. Erpek, Y. E. Sagduyu, N. Abuzainab, and D. Hartman, "Deep Learning with Interference Training for Adaptive Radar Beamforming," IEEE International Symposium on Phased Array Systems and Technology, 2022.
M. Hegarty, Y. E. Sagduyu, T. Erpek, and Y. Shi, "Deep Learning for Spectrum Awareness and Covert Communications via Unintended RF Emanations," ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) Workshop on Wireless Security and Machine Learning (WiseML), 2022.
X. Wang, M. C. Gursoy, T. Erpek, and Y. E. Sagduyu, "Collision-Aware UAV Trajectories for Data Collection via Reinforcement Learning," IEEE Global Communications Conference (GLOBECOM), 2021.
M. Costa, Y. E. Sagduyu, T. Erpek, and M. Médard, "Robust Improvement of the Age of Information by Adaptive Packet Coding," IEEE International Conference on Communications (ICC), 2021.
X. Wang, M. C. Gursoy, T. Erpek, and Y. E. Sagduyu, "Jamming-Resilient Path Planning for Multiple UAVs via Deep Reinforcement Learning," IEEE International Conference on Communications (ICC) Workshops, 2021.
Y. Shi, K. Davaslioglu, Y. E. Sagduyu, W. C. Headley, M. Fowler, and G. Green, “Deep Learning for Signal Classification in Unknown and Dynamic Spectrum Environments,” IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2019.
N. Abu Zainab, T. Erpek, K. Davaslioglu, Y. E. Sagduyu, Y. Shi, S. Mackey, M. Patel, F. Panettieri, M. Qureshi, V. Isler, A. Yener, “QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning,” IEEE Military Communications Conference (MILCOM), 2019.
S. Soltani, Y. E. Sagduyu, R. Hasan, K. Davaslioglu, H. Deng, and T. Erpek, “Real-Time and Embedded Deep Learning on FPGA for RF Signal Classification,” IEEE Military Communications Conference (MILCOM), 2019.
T. Erpek, S. Ulukus, and Y. E Sagduyu, "Interference Regime Enforcing Rate Maximization for Non-Orthogonal Multiple Access (NOMA)," IEEE International Conference on Computing, Networking and Communications (ICNC), 2019.