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11/02/2022
Defending with Errors: Approximate Computing for Robustness of Deep Neural Networks
Machine-learning architectures, such as Convolutional Neural Networks (C...
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01/05/2022
ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints
Advances in deep learning have enabled a wide range of promising applica...
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10/02/2021
Repttack: Exploiting Cloud Schedulers to Guide Co-Location Attacks
Cloud computing paradigms have emerged as a major facility to store and ...
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03/11/2021
Stochastic-HMDs: Adversarial Resilient Hardware Malware Detectors through Voltage Over-scaling
Machine learning-based hardware malware detectors (HMDs) offer a potenti...
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01/16/2020
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks
In this paper, we propose Code-Bridged Classifier (CBC), a framework for...
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06/04/2019
SPECCFI: Mitigating Spectre Attacks using CFI Informed Speculation
Spectre attacks and their many subsequent variants are a new vulnerabili...
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06/13/2018
