scholarly journals Multilayer Detection of Network Steganography

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2128
Author(s):  
Milosz Smolarczyk ◽  
Krzysztof Szczypiorski ◽  
Jakub Pawluk
Keyword(s):  
Machine Learning ◽  
Performance Analysis ◽  
Learning Algorithms ◽  
Network Protocols ◽  
Machine Learning Algorithms ◽  
New Method ◽  
Network Steganography ◽  
Large Numbers ◽  
Selective Analysis

This paper presents a new method for steganography detection in network protocols. The method is based on a multilayer approach for the selective analysis of derived and aggregated metrics utilizing machine learning algorithms. The main objective is to provide steganalysis capability for networks with large numbers of devices and connections. We discuss considerations for performance analysis and present results. We also describe a means of applying our method for multilayer detection of a popular RSTEG (Retransmission Steganography) technique.

A FRAMEWORK FOR PERFORMANCE ANALYSIS ON MACHINE LEARNING ALGORITHMS USING COVID-19 DATASET

2020 ◽  
Vol 9 (10) ◽  
pp. 8207-8215
Author(s):  
Balajee ◽  
Padmapriya ◽  
Rama Satish
Keyword(s):  
Machine Learning ◽  
Performance Analysis ◽  
Learning Algorithms ◽  
Machine Learning Algorithms

scholarly journals Performance analysis of machine learning algorithms on automated sleep staging feature sets

2021 ◽  
Author(s):  
Santosh Satapathy ◽  
D Loganathan ◽  
Hari Kishan Kondaveeti ◽  
RamaKrushna Rath
Keyword(s):  
Machine Learning ◽  
Performance Analysis ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Sleep Staging ◽  
Feature Sets
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