Search
Now showing items 1-7 of 7
Smart Edge Healthcare Data Sharing System
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Smart health systems improve the efficiency of healthcare infrastructures and biomedical systems by integrating information and technology into health and medical practices. However, reliability, scalabilty and latency are ...
Iterative per Group Feature Selection for Intrusion Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Network security is an critical subject in any distributed network. Recently, machine learning has proven their efficiency for intrusion detection. By using a comprehensive dataset with multiple attack types, a well-trained ...
Deep Reinforcement Learning Algorithm for Smart Data Compression under NOMA-Uplink Protocol
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
One of the highly promising radio access strategies for enhancing performance in the next generation cellular communications is non-orthogonal multiple access (NOMA). NOMA offers a number of advantages including better ...
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 ...
Weighted Trustworthiness for ML Based Attacks Classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Recently, machine learning techniques are gaining a lot of interest in security applications as they exhibit fast processing with real-time predictions. One of the significant challenges in the implementation of these ...
Machine Learning Based Cloud Computing Anomalies Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ...
TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Machine learning techniques are becoming mainstream in intrusion detection systems as they allow real-time response and have the ability to learn and adapt. By using a comprehensive dataset with multiple attack types, a ...