Optimal Trained Hybrid Classifier for Border Gateway Protocol Anomaly Detection

Optimal Trained Hybrid Classifier for Border Gateway Protocol Anomaly Detection

Sunita M., Sujata V. Mallapur
Copyright: © 2022 |Pages: 19
DOI: 10.4018/IJSIR.302606
OnDemand:
(Individual Articles)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Border Gateway Protocol (BGP) anomalies have interrupted network connection on a large scale, henceforth; recognizing them is of very important. Machine learning algorithms play a vital role in detecting the BGP anomalies in network. This paper intends to propose a new BGP anomaly detection method under certain processes (i) Feature Extraction and (ii) Classification. In feature extraction, certain features like "Number of Exterior Gateway Protocol (EGP) packets, Number of Interior Gateway Protocol (IGP) packets, Number of incomplete packets, Maximum Autonomous System (AS) path length, average AS-path length, packet size" etc. are extracted. Along with this, the statistical features such as mean, mode, variance, median, standard deviation, and higher-order statistical features such as kurtosis, skewness, second moment, entropy, and percentiles are also extracted. Subsequently, the classification is carried out by a hybrid classifier model that merges the Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) models.
Article Preview
Top

1. Introduction

Table 1.
Nomenclature
   Abbreviation   Description
   AS   Autonomous Systems
   BA   BAT Algorithm
   BGP   Border Gateway Protocol
   CAD   CUSUM abnormal detection
CNNConvolutional Neural Network
CSACrow Search Algorithm
DAOADestination Advertisement Object-Acknowledge
EGPExterior Gateway Protocol
EHOElephant Herding Optimization
FNRFalse Negative Rate
FPRFalse Positive Rate
FDRFalse Discovery Rate
HMMsHidden Markov Models
HEAPHijacking Event Analysis Program
IGPInterior Gateway Protocol
LSTMLong short-term memory
MFOMoth Flame Optimization
MCCMathew’s Correlation Coefficient
NPVNegative Predictive Value
NNNeural Network
NBNaive Bayes
OBLOpposition‑based learning
QSE-BGPQuantum Security Enhanced-BGP
SVMSupport Vector Machine
WOAWhale Optimization

Complete Article List

Search this Journal:
Reset
Volume 15: 1 Issue (2024)
Volume 14: 3 Issues (2023)
Volume 13: 4 Issues (2022)
Volume 12: 4 Issues (2021)
Volume 11: 4 Issues (2020)
Volume 10: 4 Issues (2019)
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing