[go: up one dir, main page]

Mhawim et al., 2022 - Google Patents

Modified Ensemble Learning Algorithms for Network Intrusion Detection System

Mhawim et al., 2022

View PDF
Document ID
3780114762377528067
Author
Mhawim D
Hashem S
Publication year
Publication venue
A Dissertation Submitted to the Department of Computer Science-University of Technology for the Degree of Doctor of Philosophy of Science in Computer Science

External Links

Snippet

ABSTRACT Network Intrusion Detection System (NIDS) is a well-known network infrastructure approach used for validating the integrity of sensitive data, making sure the availability of network systems despite adopting many techniques and algorithms (machine …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1425Traffic logging, e.g. anomaly detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55Detecting local intrusion or implementing counter-measures
    • G06F21/552Detecting local intrusion or implementing counter-measures involving long-term monitoring or reporting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416Event detection, e.g. attack signature detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6228Selecting the most significant subset of features
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1433Vulnerability analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705Clustering or classification
    • G06F17/3071Clustering or classification including class or cluster creation or modification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications

Similar Documents

Publication Publication Date Title
Kunhare et al. Particle swarm optimization and feature selection for intrusion detection system
Rincy N et al. Design and development of an efficient network intrusion detection system using machine learning techniques
Abid et al. Multilevel deep neural network approach for enhanced distributed denial-of-service attack detection and classification in software-defined Internet of Things networks
Patil et al. Majority Voting and Feature Selection Based Network Intrusion Detection System.
Ghosh et al. An efficient hybrid multilevel intrusion detection system in cloud environment
Alhabshy et al. An ameliorated multiattack network anomaly detection in distributed big data system-based enhanced stacking multiple binary classifiers
Khonde et al. Hybrid Architecture for Distributed Intrusion Detection System.
Walling et al. Performance Evaluation of Supervised Machine Learning Based Intrusion Detection with Univariate Feature Selection on NSL KDD Dataset
Hagar et al. Implementation of machine and deep learning algorithms for intrusion detection system
Walling et al. Network intrusion detection system for IoT security using machine learning and statistical based hybrid feature selection
Arshad et al. Comparative study of machine learning techniques for intrusion detection on CICIDS-2017 Dataset
Ogundele et al. A Hybrid Network Intrusion Detection Framework using Neural Network-Based Decision Tree Model
Wang et al. Application of deep neural network with frequency domain filtering in the field of intrusion detection
Mhawim et al. Modified Ensemble Learning Algorithms for Network Intrusion Detection System
Ganeshan et al. I-AHSDT: intrusion detection using adaptive dynamic directive operative fractional lion clustering and hyperbolic secant-based decision tree classifier
Manandhar A practical approach to anomaly-based intrusion detection system by outlier mining in network traffic
Ranjithkumar et al. Fuzzy Based Latent Dirichlet Allocation for Intrusion Detection in Cloud Using ML.
Salem Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques
Rifat Feature engineering on the cybersecurity dataset for deployment on software defined network
CHAHIRA Model for improving performance of network intrusion detection based on machine learning techniques
Dhillon Building effective network security frameworks using deep transfer learning techniques
Nassar et al. Network intrusion detection, literature review and some techniques comparision
Gowthami et al. Convolution Neural Network-Based Efficient Development of Intrusion Detection Using Various Deep Learning Approaches
Ampatzi How AI can Improve Intrusion Detection and Prevention System
Babu et al. Bat-Inspired Optimization for Intrusion Detection Using an Ensemble Forecasting Method.