Ihsen Alouani | DeepAI

AI Chat

Featured Co-authors

Muhammad Shafique
112 publications
Muhammad Abdullah Hanif
45 publications
Alberto Marchisio
29 publications
Rainer Leupers
25 publications
Mohamed Ali Mahjoub
21 publications
Maurizio Martina
21 publications
Farhad Merchant
20 publications
Nael Abu-Ghazaleh
15 publications
Amira Guesmi
12 publications
Ioan Marius Bilasco
11 publications
Khaled N. Khasawneh
7 publications

∙ 07/17/2023

DeepMem: ML Models as storage channels and their (mis-)applications

Machine learning (ML) models are overparameterized to support generality...

0 Md Abdullah Al Mamun, 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. ∙

∙ 04/20/2023

Jedi: Entropy-based Localization and Removal of Adversarial Patches

Real-world adversarial physical patches were shown to be successful in c...

0 Bilel Tarchoun, 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. ∙

∙ 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. ∙

∙ 10/10/2021

Adversarial Attacks in a Multi-view Setting: An Empirical Study of the Adversarial Patches Inter-view Transferability

While machine learning applications are getting mainstream owing to a de...

8 Bilel Tarchoun, et al. ∙

∙ 07/27/2021

PDF-Malware: An Overview on Threats, Detection and Evasion Attacks

In the recent years, Portable Document Format, commonly known as PDF, ha...

6 Nicolas Fleury, et al. ∙

∙ 03/11/2021

Stochastic-HMDs: Adversarial Resilient Hardware Malware Detectors through Voltage Over-scaling

Machine learning-based hardware malware detectors (HMDs) offer a potenti...

17 Md Shohidul Islam, et al. ∙

∙ 01/05/2021

An Investigation on Inherent Robustness of Posit Data Representation

As the dimensions and operating voltages of computer electronics shrink ...

0 Ihsen Alouani, et al. ∙

∙ 12/09/2020

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

Deep Learning (DL) algorithms have gained popularity owing to their prac...

14 Rida El-Allami, 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. ∙

∙ 05/16/2020

NeuroAttack: Undermining Spiking Neural Networks Security through Externally Triggered Bit-Flips

Due to their proven efficiency, machine-learning systems are deployed in...

0 Valerio Venceslai, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world