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A New Efficient Method for the detection of intrusion in 5 G andbeyond Networks using Machine Learning

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Title Statement A New Efficient Method for the detection of intrusion in 5 G andbeyond Networks using Machine Learning
 
Added Entry - Uncontrolled Name Yadav, Vikash ; ABES Engineering College, Ghaziabad
Rahul, Mayur ; UIET CSJm Kanpur
Yadav, Rishika ; Department of computer Science Engineering, Graphic Era Hill University, Dehradun
 
Uncontrolled Index Term Cryptography; Machine learning; Physical layer; Reliability; Authentication
 
Summary, etc. The 5G networks are very important to support complex application byconnecting different types of machines and devices, which provide the platform for differentspoofing attacks. Traditional physical layer and cryptography authentication methods arefacing problems in dynamic complex environment, including less reliability, securityoverhead also problem in predefined authentication system, giving protection and learn abouttime-varying attributes. In this paper, intrusion detection framework has been designed usingvarious machine learning methods with the help of physical layer attributes and to providemore efficient system to increase the security. Machine learning methods for the intelligentintrusion detection are introduced, especially for supervised and non-supervised methods.Our machine learning based intelligent intrusion detection technique for the 5G and beyondnetworks is evaluated in terms of recall, precision, accuracy and f-value are validated forunpredictable dynamics and unknown conditions of networks.
 
Publication, Distribution, Etc. Journal of Scientific & Industrial Research
2023-08-21 11:40:38
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/JSIR/article/view/38894
 
Data Source Entry Journal of Scientific & Industrial Research; ##issue.vol## 80, ##issue.no## 01 (21)
 
Language Note en