Amira Guesmi | DeepAI

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∙ 08/11/2023

Physical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook

In this paper, we present a comprehensive survey of the current trends f...

0 Amira Guesmi, et al. ∙

∙ 08/06/2023

SAAM: Stealthy Adversarial Attack on Monoculor Depth Estimation

In this paper, we investigate the vulnerability of MDE to adversarial pa...

0 Amira Guesmi, et al. ∙

∙ 05/19/2023

DAP: A Dynamic Adversarial Patch for Evading Person Detectors

In this paper, we present a novel approach for generating naturalistic a...

0 Amira Guesmi, et al. ∙

∙ 03/03/2023

Exploring Machine Learning Privacy/Utility trade-off from a hyperparameters Lens

Machine Learning (ML) architectures have been applied to several applica...

0 Ayoub Arous, et al. ∙

∙ 03/03/2023

AdvART: Adversarial Art for Camouflaged Object Detection Attacks

A majority of existing physical attacks in the real world result in cons...

4 Amira Guesmi, et al. ∙

∙ 03/02/2023

APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation

In recent years, monocular depth estimation (MDE) has witnessed a substa...

11 Amira Guesmi, et al. ∙

∙ 03/02/2023

AdvRain: Adversarial Raindrops to Attack Camera-based Smart Vision Systems

Vision-based perception modules are increasingly deployed in many applic...

0 Amira Guesmi, et al. ∙

∙ 11/02/2022

Defending with Errors: Approximate Computing for Robustness of Deep Neural Networks

Machine-learning architectures, such as Convolutional Neural Networks (C...

0 Amira Guesmi, et al. ∙

∙ 11/02/2022

a-RNA: Adversarial Radio Noise Attack to Fool Radar-based Environment Perception Systems

Due to their robustness to degraded capturing conditions, radars are wid...

0 Amira Guesmi, et al. ∙

∙ 04/18/2022

Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems

The real-world use cases of Machine Learning (ML) have exploded over the...

22 Shail Dave, et al. ∙

∙ 01/05/2022

ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints

Advances in deep learning have enabled a wide range of promising applica...

15 Amira Guesmi, et al. ∙

∙ 06/13/2020

Defensive Approximation: Enhancing CNNs Security through Approximate Computing

In the past few years, an increasing number of machine-learning and deep...

0 Amira Guesmi, et al. ∙

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