Kaleel Mahmood

40 papers A* 5A 2B 3Journal 29Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Analyzing Physical Adversarial Example Threats to Machine Learning in Election Systems. CoRR Khaleque Md. Aashiq Kamal, Surya Eada, Aayushi Verma, Subek Acharya, Adrian Yemin, Benjamin Fuller, Kaleel Mahmood
2026	J	`jnl`	On the Evidentiary Limits of Membership Inference for Copyright Auditing. CoRR Murat Bilgehan Ertan, Emirhan Böge, Min Chen, Kaleel Mahmood, Marten van Dijk
2025	J	`jnl`	Attacking all tasks at once using adversarial examples in multi-task learning. Neurocomputing Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan
2025	J	`jnl`	Attacking the spike: On the security of spiking neural networks to adversarial examples. Neurocomputing Nuo Xu, Kaleel Mahmood, Haowen Fang, Ethan Rathbun, Caiwen Ding, Wujie Wen
2025	J	`jnl`	Beyond Anonymization: Object Scrubbing for Privacy-Preserving 2D and 3D Vision Tasks. CoRR Murat Bilgehan Ertan, Ronak Sahu, Phuong Ha Nguyen, Kaleel Mahmood, Marten van Dijk
2025	A*	`conf`	Busting the Paper Ballot: Voting Meets Adversarial Machine Learning. CCS Kaleel Mahmood, Caleb Manicke, Ethan Rathbun, Aayushi Verma, Sohaib Ahmad, Nicholas Stamatakis, Laurent Michel, Benjamin Fuller
2025	J	`jnl`	Busting the Paper Ballot: Voting Meets Adversarial Machine Learning. CoRR Kaleel Mahmood, Caleb Manicke, Ethan Rathbun, Aayushi Verma, Sohaib Ahmad, Nicholas Stamatakis, Laurent Michel, Benjamin Fuller
2025	B	`conf`	Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness. IJCNN Jieren Deng, Hanbin Hong, Aaron Palmer, Xin Zhou, Jinbo Bi, Kaleel Mahmood, Yuan Hong, Derek Aguiar
2025	A	`conf`	EMTSF: Extraordinary Mixture of SOTA Models for Time Series Forecasting. ECAI Musleh Alharthi, Kaleel Mahmood, Sarosh H. Patel, Ausif Mahmood
2025	J	`jnl`	EMTSF:Extraordinary Mixture of SOTA Models for Time Series Forecasting. CoRR Musleh Alharthi, Kaleel Mahmood, Sarosh H. Patel, Ausif Mahmood
2025	A	`conf`	Efficient Context Propagating Perceiver Architectures for Auto-Regressive Language Modeling. ECAI Kaleel Mahmood, Shaoyi Huang
2025	J	`jnl`	Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning. IEEE Access Kaleel Mahmood, Ethan Rathbun, Ronak Sahu, Marten van Dijk, Sohaib Ahmad, Caiwen Ding
2024	J	`jnl`	Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness. CoRR Jieren Deng, Hanbin Hong, Aaron Palmer, Xin Zhou, Jinbo Bi, Kaleel Mahmood, Yuan Hong, Derek Aguiar
2024	J	`jnl`	Distilling Adversarial Robustness Using Heterogeneous Teachers. CoRR Jieren Deng, Aaron Palmer, Rigel Mahmood, Ethan Rathbun, Jinbo Bi, Kaleel Mahmood, Derek Aguiar
2024	J	`jnl`	Enhanced Computationally Efficient Long LoRA Inspired Perceiver Architectures for Auto-Regressive Language Modeling. CoRR Kaleel Mahmood, Shaoyi Huang
2024	J	`jnl`	Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack. CoRR Nicole Meng, Caleb Manicke, David Chen, Yingjie Lao, Caiwen Ding, Pengyu Hong, Kaleel Mahmood
2023	A*	`conf`	AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization. MICRO Yukui Luo, Nuo Xu, Hongwu Peng, Chenghong Wang, Shijin Duan, Kaleel Mahmood, Wujie Wen, Caiwen Ding, Xiaolin Xu
2023	A*	`conf`	AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. ICCV Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding
2023	J	`jnl`	AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. CoRR Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding
2023	J	`jnl`	Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models. CoRR Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan
2023	A*	`conf`	Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. DAC Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding
2023	J	`jnl`	Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. CoRR Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding
2022	B	`conf`	Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification. IEEE Big Data Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran
2022	J	`jnl`	Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks. IEEE Access Kaleel Mahmood, Rigel Mahmood, Ethan Rathbun, Marten van Dijk
2022	J	`jnl`	Besting the Black-Box: Barrier Zones for Adversarial Example Defense. IEEE Access Kaleel Mahmood, Phuong Ha Nguyen, Lam M. Nguyen, Thanh Nguyen, Marten van Dijk
2022	J	`jnl`	Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning. CoRR Ethan Rathbun, Kaleel Mahmood, Sohaib Ahmad, Caiwen Ding, Marten van Dijk
2022	B	`conf`	Inverting Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models. IJCB Sohaib Ahmad, Kaleel Mahmood, Benjamin Fuller
2022	J	`jnl`	Privacy Attacks Against Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models. CoRR Sohaib Ahmad, Benjamin Fuller, Kaleel Mahmood
2022	J	`jnl`	Securing the Spike: On the Transferabilty and Security of Spiking Neural Networks to Adversarial Examples. CoRR Nuo Xu, Kaleel Mahmood, Haowen Fang, Ethan Rathbun, Caiwen Ding, Wujie Wen
2021	J	`jnl`	Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks. CoRR Kaleel Mahmood, Rigel Mahmood, Ethan Rathbun, Marten van Dijk
2021	J	`jnl`	Beware the Black-Box: On the Robustness of Recent Defenses to Adversarial Examples. Entropy Kaleel Mahmood, Deniz Gurevin, Marten van Dijk, Phuoung Ha Nguyen
2021	A*	`conf`	On the Robustness of Vision Transformers to Adversarial Examples. ICCV Kaleel Mahmood, Rigel Mahmood, Marten van Dijk
2021	J	`jnl`	On the Robustness of Vision Transformers to Adversarial Examples. CoRR Kaleel Mahmood, Rigel Mahmood, Marten van Dijk
2020	J	`jnl`	Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples. CoRR Kaleel Mahmood, Deniz Gurevin, Marten van Dijk, Phuong Ha Nguyen
2019	J	`jnl`	BUZz: BUffer Zones for defending adversarial examples in image classification. CoRR Phuong Ha Nguyen, Kaleel Mahmood, Lam M. Nguyen, Thanh Nguyen, Marten van Dijk
2019	J	`jnl`	The Interpose PUF: Secure PUF Design against State-of-the-art Machine Learning Attacks. IACR Trans. Cryptogr. Hardw. Embed. Syst. Phuong Ha Nguyen, Durga Prasad Sahoo, Chenglu Jin, Kaleel Mahmood, Ulrich Rührmair, Marten van Dijk
2018	J	`jnl`	The Interpose PUF: Secure PUF Design against State-of-the-art Machine Learning Attacks. IACR Cryptol. ePrint Arch. Phuong Ha Nguyen, Durga Prasad Sahoo, Chenglu Jin, Kaleel Mahmood, Ulrich Rührmair, Marten van Dijk
2017	J	`jnl`	MXPUF: Secure PUF Design against State-of-the-art Modeling Attacks. IACR Cryptol. ePrint Arch. Phuong Ha Nguyen, Durga Prasad Sahoo, Chenglu Jin, Kaleel Mahmood, Marten van Dijk
2016	—	`conf`	Moving target defense for Internet of Things using context aware code partitioning and code diversification. WF-IoT Kaleel Mahmood, Devu Manikantan Shila
2014	J	`jnl`	On-Demand Asynchronous Localization for Underwater Sensor Networks. IEEE Trans. Signal Process. Patrick Carroll, Kaleel Mahmood, Shengli Zhou, Hao Zhou, Xiaoka Xu, Jun-Hong Cui