| Evaluating adversarial evasion attacks in the context of wireless communications B Flowers, RM Buehrer, WC Headley IEEE Transactions on Information Forensics and Security 15, 1102-1113, 2019 | 100 | 2019 |
| On the limitations of targeted adversarial evasion attacks against deep learning enabled modulation recognition S Bair, M DelVecchio, B Flowers, AJ Michaels, WC Headley Proceedings of the ACM Workshop on Wireless Security and Machine Learning, 25-30, 2019 | 45 | 2019 |
| When wireless security meets machine learning: Motivation, challenges, and research directions YE Sagduyu, Y Shi, T Erpek, W Headley, B Flowers, G Stantchev, Z Lu arXiv preprint arXiv:2001.08883, 2020 | 37 | 2020 |
| An rfml ecosystem: Considerations for the application of deep learning to spectrum situational awareness LJ Wong, WH Clark, B Flowers, RM Buehrer, WC Headley, AJ Michaels IEEE Open Journal of the Communications Society 2, 2243-2264, 2021 | 28* | 2021 |
| Communications aware adversarial residual networks for over the air evasion attacks B Flowers, RM Buehrer, WC Headley MILCOM 2019-2019 IEEE Military Communications Conference (MILCOM), 133-140, 2019 | 18 | 2019 |
| Effects of forward error correction on communications aware evasion attacks M DelVecchio, B Flowers, WC Headley 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile …, 2020 | 9 | 2020 |
| A UCSD view on replication and reproducibility for CPS & IoT A Yen, B Flowers, W Luo, N Nagesh, P Tueller, R Kastner, P Pannuto Proceedings of the Workshop on Benchmarking Cyber-Physical Systems and …, 2021 | 4 | 2021 |
| Real-time Forecasting of On-Time Performance in Metrorail Systems R Soper, B Flowers, S Bijinemula, B Mayer, F Khaghani, J Holt, ... 7th SIGKDD International Workshop on Urban Computing (UrbComp 2018), 2018 | 2 | 2018 |
| Countering Physical Eavesdropper Evasion with Adversarial Training KW McClintick, J Harer, B Flowers, WC Headley, AM Wyglinski IEEE Open Journal of the Communications Society 3, 1820-1833, 2022 | 1 | 2022 |
| 2 Adversarial Machine Learning: A New Threat Paradigm for Next-generation Wireless Communications YE Sagduyu, Y Shi, T Erpek, W Headley, B Flowers, G Stantchev, Z Lu, ... AI, Machine Learning and Deep Learning: A Security Perspective, 35-52, 2023 | | 2023 |
| Multi-Source Feature Fusion for Object Detection Association in Connected Vehicle Environments S Thornton, B Flowers, S Dey IEEE Access 10, 131841-131854, 2022 | | 2022 |
| Adaptive C-V2X Sidelink Communications for Vehicular Applications Beyond Safety Messages YJ Ku, B Flowers, S Thornton, S Baidya, S Dey 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), 1-6, 2022 | | 2022 |
| Low Overhead Codebook Design for mmWave Roadside Units Placed at Smart Intersections B Flowers, X Zhang, S Dey 2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile …, 2021 | | 2021 |
| Adversarial RFML: Evading Deep Learning Enabled Signal Classification BA Flowers Virginia Tech, 2019 | | 2019 |
William "Chris" HeadleyVirginia Tech National Security InstituteZweryfikowany adres z vt.edu
