Deep neural network (DNN) classifiers are potent instruments that can be used in various
security-sensitive applications. Nonetheless, they are vulnerable to certain attacks that …

The prosperity of AI and edge computing has pushed more and more well-trained DNN
models to be deployed on third-party edge devices to compose mission-critical applications …

With the recent advancements in machine learning (ML) theory, a lot of energy-efficient
neural network (NN) accelerators have been developed. However, their associated side …

Abstract Machine learning (ML) has recently been adopted in various application domains.
Usually, a well-performing ML model relies on a large volume of training data and powerful …

Physical side-channel attacks are a major threat to stealing confidential data from devices.
There has been a recent surge in such attacks on edge machine learning (ML) hardware to …

The real-world use cases of Machine Learning (ML) have exploded over the past few years.
However, the current computing infrastructure is insufficient to support all real-world …

Cryptography is an indispensable tool used to protect information in computing systems.
Billions of people all over the world use it in their daily lives without even noticing there is …

Despite considerable investments in database security, global statistics indicate an
exponential increase in data breaches. Organizations are often unaware of data breaches …

SoK Neural Network Extraction-USENIX Presentation Page 1 SoK: Neural Network Extraction
Through Physical Side Channels 15.08.2024 Péter Horváth, Dirk Lauret, Zhuoran Liu, and …

The Transformers architecture has recently emerged as a revolutionary paradigm in the field
of deep learning, particularly excelling in Natural Language Processing (NLP) and …