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IoT Anti-Jamming Strategy Using Game Theory and Neural Network
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
The internet of things (IoT) is one of the most exposed networks to attackers due to its widespread and its heterogeneity. In such networks, jamming attacks are widely used by malicious users to compromise the private and ...
Appliance identification using a histogram post-processing of 2D local binary patterns for smart grid applications
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Identifying domestic appliances in the smart grid leads to a better power usage management and further helps in detecting appliance-level abnormalities. An efficient identification can be achieved only if a robust feature ...
On the Modeling of Reliability in Extreme Edge Computing Systems
(
IEEE
, 2022 , Conference Paper)
Extreme edge computing (EEC) refers to the end-most part of edge computing wherein computational tasks and edge services are deployed only on extreme edge devices (EEDs). EEDs are consumer or user-owned devices that offer ...
Proportionally fair approach for tor's circuits scheduling
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
The number of users adopting Tor to protect their online privacy is increasing rapidly. With a limited number of volunteered relays in the network, the number of clients' connections sharing the same relays is increasing ...
Patient-Driven Network Selection in multi-RAT Health Systems Using Deep Reinforcement Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
The recent pandemic along with the rapid increase in the number of patients that require continuous remote monitoring imposes several challenges to support the high quality of services (QoS) in remote health applications. ...
Hypertension Prediction Using Optimal Random Forest and Real Medical Data
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Long-lasting and difficult-to-treat, hypertension frequently leads to serious and life-threatening diseases. As a result, early risk assessment and prevention of hypertension are crucial. The majority of research currently ...
RL-Assisted Energy-Aware User-Edge Association for IoT-based Hierarchical Federated Learning
(2022 , Conference Paper)
The extremely heavy global reliance on IoT devices is causing enormous amounts of data to be gathered and shared in IoT networks. Such data need to efficiently be used in training and deploying of powerful artificially ...
A Deep Learning Model for LoRa Signals Classification Using Cyclostationay Features
(
IEEE Computer Society
, 2021 , Conference Paper)
With the witnessed exponential growth of Internet of Things (IoT) nodes deployment following the emerging applications, multiple variants of technologies have been proposed to handle the IoT requirements. Among the proposed ...
DistPrivacy: Privacy-Aware Distributed Deep Neural Networks in IoT surveillance systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
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 paradigm in terms of memory and computation, ...
Smart City Perspectives in the Context of Qatar
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference Paper)
The smart city concept is being implemented in different countries. In order to make such a concept successful, countries need to invest heavily in information and communication technology and provide opportunity to utilize ...