A robust analysis of adversarial attacks on federated learning environments
Federated Learning is a growing branch of Artificial Intelligence with the wide usage of
mobile computing and IoT technologies. Since this technology uses distributed computing …
mobile computing and IoT technologies. Since this technology uses distributed computing …
Private retrieval, computing, and learning: Recent progress and future challenges
Most of our lives are conducted in the cyberspace. The human notion of privacy translates
into a cyber notion of privacy on many functions that take place in the cyberspace. This …
into a cyber notion of privacy on many functions that take place in the cyberspace. This …
Secure and provenance enhanced internet of health things framework: A blockchain managed federated learning approach
Recent advancements in the Internet of Health Things (IoHT) have ushered in the wide
adoption of IoT devices in our daily health management. For IoHT data to be acceptable by …
adoption of IoT devices in our daily health management. For IoHT data to be acceptable by …
On privacy and personalization in cross-silo federated learning
While the application of differential privacy (DP) has been well-studied in cross-device
federated learning (FL), there is a lack of work considering DP and its implications for cross …
federated learning (FL), there is a lack of work considering DP and its implications for cross …
[HTML][HTML] Safeguarding cross-silo federated learning with local differential privacy
Federated Learning (FL) is a new computing paradigm in privacy-preserving Machine
Learning (ML), where the ML model is trained in a decentralized manner by the clients …
Learning (ML), where the ML model is trained in a decentralized manner by the clients …
Enabling long-term cooperation in cross-silo federated learning: A repeated game perspective
Cross-silo federated learning (FL) is a distributed learning approach where clients of the
same interest train a global model cooperatively while keeping their local data private. The …
same interest train a global model cooperatively while keeping their local data private. The …
VARF: An incentive mechanism of cross-silo federated learning in MEC
Cross-silo federated learning (FL) is a privacy-preserving distributed machine learning
where organizations acting as clients cooperatively train a global model without uploading …
where organizations acting as clients cooperatively train a global model without uploading …
Duopoly business competition in cross-silo federated learning
In cross-silo federated learning, clients (eg, organizations) collaboratively train a global
model using private local data. In practice, clients may be not only collaborators but also …
model using private local data. In practice, clients may be not only collaborators but also …
Secure federated learning architecture for fuzzy classifier in healthcare environment
There have been many developments in recent years based on the Internet of Things (IoT),
particularly for managing data pertaining to healthcare as it is now known as the Internet of …
particularly for managing data pertaining to healthcare as it is now known as the Internet of …
Incentive-aware autonomous client participation in federated learning
Federated learning (FL) emerges as a promising paradigm to enable a federation of clients
to train a machine learning model in a privacy-preserving manner. Most existing works …
to train a machine learning model in a privacy-preserving manner. Most existing works …