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08/31/2023
Fault Injection and Safe-Error Attack for Extraction of Embedded Neural Network Models
Model extraction emerges as a critical security threat with attack vecto...
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08/31/2023
Fault Injection on Embedded Neural Networks: Impact of a Single Instruction Skip
With the large-scale integration and use of neural network models, espec...
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04/25/2023
Evaluation of Parameter-based Attacks against Embedded Neural Networks with Laser Injection
Upcoming certification actions related to the security of machine learni...
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03/19/2023
Evaluation of Convolution Primitives for Embedded Neural Networks on 32-bit Microcontrollers
Deploying neural networks on constrained hardware platforms such as 32-b...
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11/10/2022
A Practical Introduction to Side-Channel Extraction of Deep Neural Network Parameters
Model extraction is a major threat for embedded deep neural network mode...
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09/28/2022
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural Networks
Deep neural network models are massively deployed on a wide variety of h...
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05/04/2021
An Overview of Laser Injection against Embedded Neural Network Models
For many IoT domains, Machine Learning and more particularly Deep Learni...
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05/04/2021
A Review of Confidentiality Threats Against Embedded Neural Network Models
Utilization of Machine Learning (ML) algorithms, especially Deep Neural ...
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04/26/2021
Impact of Spatial Frequency Based Constraints on Adversarial Robustness
Adversarial examples mainly exploit changes to input pixels to which hum...
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04/10/2020
Luring of Adversarial Perturbations
The growing interest for adversarial examples, i.e. maliciously modified...
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09/27/2019
