Development of secured data transmission using machine learning-based discrete-time partially observed Markov model and energy optimization in cognitive radio networks

The cognitive radio network (CR) is a primary and promising technology to distribute the spectrum assignment to an unlicensed user (secondary users) which is not utilized by the licensed user (primary user).The cognitive radio network frames a reactive security policy to enhance the energy monitorin...

Full description

Saved in:
Bibliographic Details
Published in:Neural computing & applications Vol. 32; no. 1; pp. 151 - 161
Main Authors: Vimal, S., Kalaivani, L., Kaliappan, M., Suresh, A., Gao, Xiao-Zhi, Varatharajan, R.
Format: Journal Article
Language:English
Published: London Springer London 01.01.2020
Springer Nature B.V
Subjects:
Algorithms
Artificial Intelligence
Brain- Inspired computing and Machine learning for Brain Health
Cognitive radio
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer simulation
Data communications
Data Mining and Knowledge Discovery
Data transmission
Encryption
Energy
Energy consumption
Energy levels
Image Processing and Computer Vision
Machine learning
Markov chains
Markov processes
Monitoring
Network security
Optimization
Probability and Statistics in Computer Science
Radio networks
Security
Wireless communication
Éclat algorithm
Cognitive radio networks
Byzantine attack
Machine learning
ISSN:0941-0643, 1433-3058
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The cognitive radio network (CR) is a primary and promising technology to distribute the spectrum assignment to an unlicensed user (secondary users) which is not utilized by the licensed user (primary user).The cognitive radio network frames a reactive security policy to enhance the energy monitoring while using the CR network primary channels. The CR network has a good amount of energy capacity using battery resource and accesses the data communication via the time-slotted channel. The data communication with moderate energy-level utilization during transmission is a great challenge in CR network security monitoring, since intruders may often attack the network in reducing the energy level of the PU or SU. The framework used to secure the communication is using the discrete-time partially observed Markov decision process. This system proposes a modern data communication-secured scheme using private key encryption with the sensing results, and eclat algorithm has been proposed for energy detection and Byzantine attack prediction. The data communication is secured using the AES algorithm at the CR network, and the simulation provides the best effort-efficient energy usage and security.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-018-3788-3