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Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems and speech processing applications to robotics ...
Dynamic Network Slicing and Resource Allocation for 5G-and-Beyond Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
5G networks are designed not only to transport data, but also to process them while supporting a vast number of services with different key Performance Indicators (KPIs). Network virtualization has emerged to enable this ...
UAVs Smart heuristics for Target Coverage and Path Planning Through Strategic Locations
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
The affordability and deployment-flexibility of Unmanned Air Vehicles (UAVs) have ignited the development of many smart applications, including surveillance, disaster management, and smart farming. Drone's energy consumption ...
FEDGAN-IDS: Privacy-preserving IDS using GAN and Federated Learning
(
Elsevier
, 2022 , Article)
Federated Learning (FL) is a promising distributed training model that aims to minimize the data sharing to enhance privacy and performance. FL requires sufficient and diverse training data to build efficient models. Lack ...
Secure Wireless Sensor Networks for Anti-Jamming Strategy Based on Game Theory
(
IEEE
, 2023 , Conference Paper)
The Wireless Sensor Networks (WSN) are designed to remotely monitor and control specific physical or environmental conditions. However, due to the open nature of WSN, many threats and attacks may arise by malicious users ...
Machine Learning Techniques for Network Anomaly Detection: A Survey
(
IEEE
, 2020 , Conference Paper)
Nowadays, distributed data processing in cloud computing has gained increasing attention from many researchers. The intense transfer of data has made the network an attractive and vulnerable target for attackers to exploit ...
Hybrid Machine Learning for Network Anomaly Intrusion Detection
(
IEEE
, 2020 , Conference Paper)
In this paper, a hybrid approach of combing two machine learning algorithms is proposed to detect the different possible attacks by performing effective feature selection and classification. This system uses Random Forest ...
RL-DistPrivacy: Privacy-Aware Distributed Deep Inference for Low Latency IoT Systems
(
IEEE Computer Society
, 2022 , Article)
Although Deep Neural Networks (DNN) have become the backbone technology of several ubiquitous applications, their deployment in resource-constrained machines, e.g., Internet of Things (IoT) devices, is still challenging. ...
On Designing Smart Agents for Service Provisioning in Blockchain-Powered Systems
(
IEEE Computer Society
, 2022 , Article)
Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users' Quality of Experience (QoE) and the operation cost endured by providers. These ...
Hierarchical Federated Learning over HetNets enabled by Wireless Energy Transfer
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Training centralized machine learning (ML) models becomes infeasible in wireless networks due to the increasing number of internet of things (IoT) and mobile devices and the prevalence of the learning algorithms to adapt ...