Abstract
In this paper, we propose a learning method for the security of CRN which can be used to identify known signals and thus report any unexpected behavior or signals in the network.
Original language | American English |
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Title of host publication | NAECON 2018 - IEEE National Aerospace and Electronics Conference |
Publisher | IEEE |
Pages | 137-143 |
Number of pages | 7 |
ISBN (Electronic) | 978-1-5386-6557-2, 978-1-5386-6556-5 |
ISBN (Print) | 978-1-5386-6558-9 |
DOIs | |
State | Published - Dec 3 2018 |
Event | 2018 IEEE National Aerospace and Electronics Conference, NAECON 2018 - Dayton, United States Duration: Jul 23 2018 → Jul 26 2018 |
Conference
Conference | 2018 IEEE National Aerospace and Electronics Conference, NAECON 2018 |
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Country/Territory | United States |
City | Dayton |
Period | 7/23/18 → 7/26/18 |
ASJC Scopus Subject Areas
- Computer Networks and Communications
- Computer Science Applications
- Control and Systems Engineering
- Electrical and Electronic Engineering
Keywords
- Cognitive Radio Network
- CRN security
- Neural Network
- SDR
Disciplines
- Aerospace Engineering
- Electrical and Computer Engineering