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RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ...
Privacy-Preserving Distributed IDS Using Incremental Learning for IoT Health Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Existing techniques for incremental learning are computationally expensive and produce duplicate features leading to higher false positive and true negative rates. We propose a novel privacy-preserving intrusion detection ...
Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Commercial unmanned aerial vehicles, or drones, are getting increasingly popular in the last few years. The fact that these drones are highly accessible to public may bring a range of security and technical issues to ...
Hierarchical Federated Learning for Collaborative IDS in IoT Applications
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
As the Internet-of-Things devices are being very widely adopted in all fields, such as smart houses, healthcare, and transportation, extremely huge amounts of data are being gathered, shared, and processed. This fact raises ...
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an ...