In edge computing environments, app vendors can cache their data to be s...
Federated learning (FL) enables multiple clients to collaboratively trai...
Deterministic Networking (DetNet) is a rising technology that offers
det...
As acquiring manual labels on data could be costly, unsupervised domain
...
Federated Learning (FL) is pervasive in privacy-focused IoT environments...
Fully Homomorphic Encryption (FHE) is a key technology enabling
privacy-...
The rapidly expanding number of Internet of Things (IoT) devices is
gene...
The transferability of adversarial examples (AEs) across diverse models ...
Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer...
Transferability of adversarial examples is of critical importance to lau...
Starting from the local structures to study hierarchical trees is a comm...
In response to the threat of adversarial examples, adversarial training
...
The distributed denial of service (DDoS) attack is detrimental to busine...
The processor failures in a multiprocessor system have a negative impact...
The distributed denial of service (DDoS) attack is detrimental to busine...
Mobile crowdsensing (MCS) is an emerging sensing data collection pattern...
High cost of training time caused by multi-step adversarial example
gene...
Federated learning has become prevalent in medical diagnosis due to its
...
In this paper, we propose a privacy-preserving medical treatment system ...
Getting access to labelled datasets in certain sensitive application dom...
The application of federated extreme gradient boosting to mobile crowdse...
Federated learning is a decentralized machine learning technique that ev...
Android malware detection is a critical step towards building a security...
A learning federation is composed of multiple participants who use the
f...
In this paper, we propose a framework for lightning-fast privacy-preserv...
The state-of-the-art federated learning brings a new direction for the d...
The recent proliferation of smart devices has given rise to ubiquitous
c...