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List of publications is given below. Please visit Google Scholar for more updates.

Publications

Journal Papers
  1. 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, June 2022.
  2. B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, "Adversarial Machine Learning for NextG Covert Communications using Multiple Antennas," Entropy 24, no. 8: 1047, 2022.
Conference Papers
  1. B. Kim, J. Kong, T. J. Moore, and F. T. Dagefu, "Reinforcement Learning for Covert Heterogeneous Wireless Network Routing with a Threat Region," IEEE Consumer Communications & Networking Conference, January 2025.
  2. B. Kim, J. Kong, T. J. Moore, and F. T. Dagefu, "Reinforcement Learning Based Covert Routing with Node Failure Resiliency for Heterogeneous Networks," IEEE Military Communications Conference, October 2024.
  3. C. Tassie, B. Kim, J. Groen, M. Belgiovine, and K. R. Chowdhury, “Leveraging Explainable AI for Reducing Queries of Performance Indicators in Open RAN,” IEEE International Conference on Communications (ICC), June 2024.
  4. J. Groen, M. Belgiovine, U. Utku, B. Kim, and K. R. Chowdhury, “TRACTOR: Traffic Analysis and Classification Tool for Open RAN,” IEEE International Conference on Communications (ICC), June 2024.
  5. A. Z. Chiejina, B. Kim, K. R. Chowdhury, and V. Shah, “System-level Analysis of Adversarial Attacks and Defenses on Intelligence in O-RAN based Cellular Networks,” ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec), May. 2024.
  6. N. N. Sapavath*, B. Kim*, K. R. Chowdhury, and V. K. Shah, "Experimental Study of Adversarial Attacks on ML-based xApps in O-RAN," IEEE Global Communications Conference (Globecom), Dec. 2023.
  7. J. Groen, B. Kim, and K. R. Chowdhury, "The Cost of Securing O-RAN," IEEE International Conference on Communications (ICC), May 2023.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. H. Kim, J. Kang, S. Jeong, K. E. Lee, and J. Kang, "Secure Beamforming and Self-Energy Recycling with Full-Duplex Wireless-Powered Relay," IEEE Consumer Communications and Networking Conference (CCNC), 2016.
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