Deep Neural Network (DNN) models are often deployed in resource-sharing
...
Vertical federated learning (VFL) has recently emerged as an appealing
d...
Denoising diffusion probabilistic models (DDPMs) are a class of powerful...
The backdoor attack poses a new security threat to deep neural networks....
Federated learning (FL) is the most popular distributed machine learning...
Training highly performant deep neural networks (DNNs) typically require...
Object detection is the foundation of various critical computer-vision t...
To improve the modeling resilience of silicon strong physical unclonable...
Federated Learning (FL), a distributed machine learning paradigm, has be...
Split learning (SL) enables data privacy preservation by allowing client...
Backdoor attacks have been a critical threat to deep neural network (DNN...
The problem of scheduling unrelated machines has been studied since the
...
Recent years have witnessed the rapid growth of federated learning (FL),...
As a well-known physical unclonable function that can provide huge numbe...
Federated learning (FL) trains a global model across a number of
decentr...
What is the best way to exploit extra data – be it unlabeled data from t...
Deep learning models have been shown to be vulnerable to recent backdoor...
Rowhammer has drawn much attention from both academia and industry in th...
A backdoor deep learning (DL) model behaves normally upon clean inputs b...
Training high-performing deep learning models require a rich amount of d...
Physical Unclonable Function (PUF) is a hardware security primitive with...
Given the ubiquity of memory in commodity electronic devices, fingerprin...
There is currently a burgeoning demand for deploying deep learning (DL)
...
Though deep neural network models exhibit outstanding performance for va...
Collaborative inference has recently emerged as an intriguing framework ...
Emerging ultra-low-power tiny scale computing devices in Cyber-Physical
...
Federated learning (FL) and split learning (SL) are state-of-the-art
dis...
There are now many adversarial attacks for natural language processing
s...
Rowhammer attacks that corrupt level-1 page tables to gain kernel privil...
This paper computes a distance between tasks modeled as joint distributi...
As an essential processing step in computer vision applications, image
r...
Due to the strong analytical ability of big data, deep learning has been...
Artificial intelligence (AI) has been applied in phishing email detectio...
This work provides the community with a timely comprehensive review of
b...
This work is the first attempt to evaluate and compare felderated learni...
A new collaborative learning, called split learning, was recently introd...
This paper employs a formal connection of machine learning with
thermody...
This work corroborates a run-time Trojan detection method exploiting STR...
The fundamental assignment problem is in search of welfare maximization
...
Recent trojan attacks on deep neural network (DNN) models are one insidi...
Recently, we have witnessed the emergence of intermittently powered
comp...
A securely maintained key is the premise upon which data stored and
tran...
A physical unclonable function (PUF) generates hardware intrinsic volati...
The simplicity of deployment and perpetual operation of energy harvestin...
The physical unclonable function (PUF), alike fingerprint of human being...