RL-PDNN: Reinforcement learning for privacy-aware distributed neural networks in IoT systems
Due to their high computational and memory demand, deep learning applications are mainly
restricted to high-performance units, eg, cloud and edge servers. Particularly, in Internet of …
restricted to high-performance units, eg, cloud and edge servers. Particularly, in Internet of …
Learning the optimal partition for collaborative DNN training with privacy requirements
With the growth of intelligent Internet of Things (IoT) applications and services, deep neural
network (DNN) has become the core method to power and enable increased functionality in …
network (DNN) has become the core method to power and enable increased functionality in …
Privacy-aware edge computing based on adaptive DNN partitioning
Recent years have witnessed deep neural networks (DNNs) become the de facto tool in
many applications such as image classification and speech recognition. But significant …
many applications such as image classification and speech recognition. But significant …
[HTML][HTML] Multi-agent reinforcement learning for privacy-aware distributed CNN in heterogeneous IoT surveillance systems
Abstract Although Deep Neural Networks (DNN) have become the backbone technology of
several Internet of Things (IoT) applications, their execution in resource-constrained devices …
several Internet of Things (IoT) applications, their execution in resource-constrained devices …
RL-DistPrivacy: Privacy-aware distributed deep inference for low latency IoT systems
Although Deep Neural Networks (DNN) have become the backbone technology of several
ubiquitous applications, their deployment in resource-constrained machines, eg, Internet of …
ubiquitous applications, their deployment in resource-constrained machines, eg, Internet of …
PADL: Privacy-aware and asynchronous deep learning for IoT applications
As a promising data-driven technology, deep learning has been widely employed in a
variety of Internet-of-Things (IoT) applications. Examples include automated navigation …
variety of Internet-of-Things (IoT) applications. Examples include automated navigation …
Distprivacy: Privacy-aware distributed deep neural networks in iot surveillance systems
With the emergence of smart cities, Internet of Things (IoT) devices as well as deep learning
technologies have witnessed an increasing adoption. To support the requirements of such …
technologies have witnessed an increasing adoption. To support the requirements of such …
Efficient privacy-preserving federated learning for resource-constrained edge devices
A large volume of data is generated by ubiquitous Internet-of-Things (IoT) devices and
utilized to train machine learning models by IoT manufacturers to provide users with better …
utilized to train machine learning models by IoT manufacturers to provide users with better …
LEP-CNN: A lightweight edge device assisted privacy-preserving CNN inference solution for IoT
Supporting convolutional neural network (CNN) inference on resource-constrained IoT
devices in a timely manner has been an outstanding challenge for emerging smart systems …
devices in a timely manner has been an outstanding challenge for emerging smart systems …
Game theory based privacy preserving approach for collaborative deep learning in iot
The exponential growth of Internet of Things (IoT) has become a transcending force in
creating innovative smart devices and connected domains including smart homes …
creating innovative smart devices and connected domains including smart homes …