Kaleel Mahmood

Orcid: 0000-0002-7672-4449

According to our database1, Kaleel Mahmood authored at least 20 papers between 2014 and 2024.

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Bibliography

2024
Distilling Adversarial Robustness Using Heterogeneous Teachers.
CoRR, 2024

2023
Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models.
CoRR, 2023

AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization.
Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning.
CoRR, 2022

Privacy Attacks Against Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models.
CoRR, 2022

Securing the Spike: On the Transferabilty and Security of Spiking Neural Networks to Adversarial Examples.
CoRR, 2022

Besting the Black-Box: Barrier Zones for Adversarial Example Defense.
IEEE Access, 2022

Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks.
IEEE Access, 2022

Inverting Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models.
Proceedings of the IEEE International Joint Conference on Biometrics, 2022

Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Beware the Black-Box: On the Robustness of Recent Defenses to Adversarial Examples.
Entropy, 2021

On the Robustness of Vision Transformers to Adversarial Examples.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples.
CoRR, 2020

2019
The Interpose PUF: Secure PUF Design against State-of-the-art Machine Learning Attacks.
IACR Trans. Cryptogr. Hardw. Embed. Syst., 2019

BUZz: BUffer Zones for defending adversarial examples in image classification.
CoRR, 2019

2017
MXPUF: Secure PUF Design against State-of-the-art Modeling Attacks.
IACR Cryptol. ePrint Arch., 2017

2016
Moving target defense for Internet of Things using context aware code partitioning and code diversification.
Proceedings of the 3rd IEEE World Forum on Internet of Things, 2016

2014
On-Demand Asynchronous Localization for Underwater Sensor Networks.
IEEE Trans. Signal Process., 2014


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