Intrusion detection for secure social internet of things based on collaborative edge computing: a generative adversarial network-based approach
The Social Internet of Things (SIoT) now penetrates our daily lives. As a strategy to alleviate
the escalation of resource congestion, collaborative edge computing (CEC) has become a …
the escalation of resource congestion, collaborative edge computing (CEC) has become a …
Data fusion and transfer learning empowered granular trust evaluation for Internet of Things
Abstract In the Internet of Things (IoT), a huge amount of valuable data is generated by
various IoT applications. As the IoT technologies become more complex, the attack methods …
various IoT applications. As the IoT technologies become more complex, the attack methods …
Disbezant: secure and robust federated learning against byzantine attack in iot-enabled mts
With the intelligentization of Maritime Transportation System (MTS), Internet of Thing (IoT)
and machine learning technologies have been widely used to achieve the intelligent control …
and machine learning technologies have been widely used to achieve the intelligent control …
A reliable and efficient task offloading strategy based on multifeedback trust mechanism for IoT edge computing
W Kong, X Li, L Hou, J Yuan, Y Gao… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Facing multidemand tasks and massive heterogeneous resources in an IoT edge computing
environment, it is a challenge to obtain reliable and quick response service and allocate …
environment, it is a challenge to obtain reliable and quick response service and allocate …
Toward secure and efficient deep learning inference in dependable IoT systems
The rapid development of deep learning (DL) enables resource-constrained systems and
devices [eg, Internet of Things (IoT)] to perform sophisticated artificial intelligence (AI) …
devices [eg, Internet of Things (IoT)] to perform sophisticated artificial intelligence (AI) …
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 …
A survey of machine and deep learning methods for privacy protection in the internet of things
Recent advances in hardware and information technology have accelerated the proliferation
of smart and interconnected devices facilitating the rapid development of the Internet of …
of smart and interconnected devices facilitating the rapid development of the Internet of …
Asteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices
On-device Deep Neural Network (DNN) training has been recognized as crucial for privacy-
preserving machine learning at the edge. However, the intensive training workload and …
preserving machine learning at the edge. However, the intensive training workload and …
Enabling privacy-preserving, compute-and data-intensive computing using heterogeneous trusted execution environment
There is an urgent demand for privacy-preserving techniques capable of supporting
compute and data intensive (CDI) computing in the era of big data. However, none of …
compute and data intensive (CDI) computing in the era of big data. However, none of …
An Adaptive Communication‐Efficient Federated Learning to Resist Gradient‐Based Reconstruction Attacks
Y Li, Y Li, H Xu, S Ren - Security and Communication Networks, 2021 - Wiley Online Library
The widely deployed devices in Internet of Things (IoT) have opened up a large amount of
IoT data. Recently, federated learning emerges as a promising solution aiming to protect …
IoT data. Recently, federated learning emerges as a promising solution aiming to protect …