Papers

My list of papers (by topic) can be found here.

Adversarial Machine Learning

  1. K. Mahmood, R. Mahmood and M. van Dijk, “On the Robustness of Vision Transformers to Adversarial Examples”, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) 2021, paper available here.
  2. K. Mahmood, D. Gurevin, M. van Dijk and P. Nguyen, “Beware the Black-Box: On the Robustness of Recent Defenses to Adversarial Examples”, Entropy, 23, 1359, 2021, paper available here.
  3. K. Mahmood, P. H. Nguyen, L. M. Nguyen, T. Nguyen and M. Van Dijk, “Besting the Black-Box: Barrier Zones for Adversarial Example Defense,” in IEEE Access, vol. 10, pp. 1451-1474, 2022, paper available here.
  4. K. Mahmood, R. Mahmood, E. Rathbun and M. van Dijk, “Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks”, IEEE Access, vol. 10, pp. 998-1019, 2022, paper available here.
  5. Y. Wang, N. Xu, S. Huang, K. Mahmood, D. Guo, C. Ding, W. Wen, and S. Rajasekaran, “Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification”, in 2022 IEEE International Conference on Big Data, pp. 5823-5832, 2022, paper available here.
  6. S. Ahmad, B. Fuller and K. Mahmood, “Inverting Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models”, IEEE International Joint Conference on Biometrics (IJCB), 2022, paper available here.
  7. H. Peng, S. Huang, T. Zhou, Y. Luo, C. Wang, Z. Wang, J. Zhao, X. Xie, A. Li, T. Geng, K. Mahmood, W. Wen, X. Xu, C. Ding, “AutoReP: Automatic ReLU Replacement for Fast Private Network Inference”, (in submission) arXiv preprint, arXiv:2308.10134, 2023, E-print available here.

Adversarial Machine Learning in New Domains (Spiking Neural Networks, Multi-task Learning and Game Theory)

  1. N. Xu, K. Mahmood, H. Fang, E. Rathbun, C. Ding and W. Wen, “Securing the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples”, (in submission) arXiv preprint, arXiv:2209.03358, 2022, E-print available here.
  2. E. Rathbun, K. Mahmood, S. Ahmad, C. Ding and M. van Dijk, “Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning”, (in submission) arXiv preprint arXiv:2211.14669, 2022, E-print available here.
  3. L. Zhang, X. Liu, K. Mahmood, C. Ding and H. Guan. “Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models”, (in submission) arXiv preprint, arXiv:2305.12066, 2023, E-print available here.

Pure Machine Learning

  1. S. Huang, H. Fang, K. Mahmood, et al., “Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration”, (in submission) arXiv preprint, arXiv:2304.12214, 2023, E-print available here.

Hardware Security

  1. P. Nguyen, D. Sahoo, C. Jin, K. Mahmood and M. van Dijk, “The Interpose PUF: Secure PUF Design against State-of-the-art Machine Learning Attacks”, Conference on Cryptographic Hardware and Embedded Systems, Volume 4, 2019. Paper available online.
  2. K. Mahmood, D. M. Shila, “Moving target defense for Internet of Things using context aware code partitioning and code diversification”, 2016 IEEE 3rd World Forum on Internet of Things, pp. 329-330, 2016. Paper available online.
  3. K. Mahmood, P. Carmona, S. Shahbazmohamadi, F. Pla, and B. Javidi, “Real-time automated counterfeit integrated circuit detection using x-ray microscopy”, in Applied Optics, vol. 54, D25-D32, 2015. Paper available online.

Signal Processing and Underwater Sensor Networks 

  1. K. Mahmood, K. Domrese, P. Carroll, H. Zhou, X. Xu, S. Zhou, “Implementation and Field Testing of On-Demand Asynchronous Localization”, in Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, Nov. 3-6, 2013.
  2. P. Carroll, K. Mahmood, S. Zhou, H. Zhou, X. Xu, J.-H. Cui, “On-Demand Asynchronous Localization for Underwater Sensor Networks”, in IEEE Transactions on Signal Processing, vol.62, no.13, pp.3337-3348, July 1, 2014.
  3. X. Xu, S. Zhou, K. Mahmood, L. Wei, J.-H. Cui, “Study of Class-D Power Amplifiers for Underwater Acoustic OFDM Transmissions”, in Oceans/IEEE, San Diego, Sept. 23-27, 2013.
  4. P. Carroll, S. Zhou, K. Mahmood, H. Zhou, X. Xu, and J.-H. Cui, “On-Demand Asynchronous Localization for Underwater Sensor Networks”, in Proc. of IEEE/MTS OCEANS conference, Hampton Roads, Virginia, Oct. 14-19, 2012.
  5. B. Kivilcim, D. Zhou, Z. Shi, and K. Mahmood, “An Efficient Approach to Wireless Firmware Update Based on Erasure Correction Coding”, International Conference on Information Technology-New Generations, pp. 431-435, paper available here.