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On the Robustness of Vision Transformers to Adversarial Examples

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021, p.7818-7827

2021

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Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks

IEEE access, 2022, Vol.10, p.998-1019

2022

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Beware the Black-Box: On the Robustness of Recent Defenses to Adversarial Examples

Entropy (Basel, Switzerland), 2021-10, Vol.23 (10), p.1359

2021

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Besting the Black-Box: Barrier Zones for Adversarial Example Defense

IEEE access, 2022, Vol.10, p.1451-1474

2022

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The Interpose PUF: Secure PUF Design against State-of-the-art Machine Learning Attacks

IACR transactions on cryptographic hardware and embedded systems, 2019-08, p.243-290

2019

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Real-time automated counterfeit integrated circuit detection using x-ray microscopy

Applied Optics, 2015-05, Vol.54 (13), p.D25

2015

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On-Demand Asynchronous Localization for Underwater Sensor Networks

IEEE transactions on signal processing, 2014-07, Vol.62 (13), p.3337-3348

2014

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Designing Deep Networks for Adversarial Robustness and Security

Mahmood, Kaleel R

2022

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Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration

2023 60th ACM/IEEE Design Automation Conference (DAC), 2023, p.1-6

2023

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Inverting Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models

2022 IEEE International Joint Conference on Biometrics (IJCB), 2022, p.1-11

2022

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Moving target defense for Internet of Things using context aware code partitioning and code diversification

2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), 2016, p.329-330

2016

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On-demand asynchronous localization for underwater sensor networks

2012 Oceans, 2012, p.1-4

2012

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Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification

2022 IEEE International Conference on Big Data (Big Data), 2022, p.5823-5832

2022

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AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization

2023 56th IEEE/ACM International Symposium on Microarchitecture (MICRO), 2023, p.628-640

2023

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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, p.628-640

2023

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Study of class-D power amplifiers for underwater acoustic OFDM transmissions

2013 OCEANS - San Diego, 2013, p.1-3

2013

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An Efficient Approach to Wireless Firmware Update Based on Erasure Correction Coding

ITNG 2023 20th International Conference on Information Technology-New Generations, p.431-435

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On the Robustness of Vision Transformers to Adversarial Examples

Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks

Beware the Black-Box: On the Robustness of Recent Defenses to Adversarial Examples

Besting the Black-Box: Barrier Zones for Adversarial Example Defense

The Interpose PUF: Secure PUF Design against State-of-the-art Machine Learning Attacks

Real-time automated counterfeit integrated circuit detection using x-ray microscopy

On-Demand Asynchronous Localization for Underwater Sensor Networks

Designing Deep Networks for Adversarial Robustness and Security

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration

Inverting Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models

Moving target defense for Internet of Things using context aware code partitioning and code diversification

On-demand asynchronous localization for underwater sensor networks

Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification

AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization

AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization

Study of class-D power amplifiers for underwater acoustic OFDM transmissions

An Efficient Approach to Wireless Firmware Update Based on Erasure Correction Coding

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