[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

D'hooge et al., 2019 - Google Patents

In-depth comparative evaluation of supervised machine learning approaches for detection of cybersecurity threats

D'hooge et al., 2019

View PDF
Document ID
15796510828075897425
Author
D'hooge L
Wauters T
Volckaert B
De Turck F
Publication year
Publication venue
4th International Conference on Internet of Things, Big Data and Security (IoTBDS)

External Links

Snippet

This paper describes the process and results of analyzing CICIDS2017, a modern, labeled data set for testing intrusion detection systems. The data set is divided into several days, each pertaining to different attack classes (Dos, DDoS, infiltration, botnet, etc.). A pipeline …
Continue reading at biblio.ugent.be (PDF) (other versions)

Classifications

    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • 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

Similar Documents

Publication Publication Date Title
D’hooge et al. Inter-dataset generalization strength of supervised machine learning methods for intrusion detection
Serpen et al. Host-based misuse intrusion detection using PCA feature extraction and kNN classification algorithms
Jha et al. Intrusion detection system using support vector machine
Bouke et al. An intelligent DDoS attack detection tree-based model using Gini index feature selection method
D'hooge et al. In-depth comparative evaluation of supervised machine learning approaches for detection of cybersecurity threats
Laurenza et al. Malware triage for early identification of advanced persistent threat activities
Dutt et al. Real-time hybrid intrusion detection system using machine learning techniques
Alaeiyan et al. A multilabel fuzzy relevance clustering system for malware attack attribution in the edge layer of cyber-physical networks
Nguyen et al. An efficient local region and clustering-based ensemble system for intrusion detection
Zhang et al. Based on multi-features and clustering ensemble method for automatic malware categorization
Nakashima et al. Automated feature selection for anomaly detection in network traffic data
Aghaei et al. Ensemble classifier for misuse detection using N-gram feature vectors through operating system call traces
Saheed et al. An efficient hybridization of k-means and genetic algorithm based on support vector machine for cyber intrusion detection system
DR et al. Malicious URL Detection and Classification Analysis using Machine Learning Models
Alhabshy et al. An ameliorated multiattack network anomaly detection in distributed big data system-based enhanced stacking multiple binary classifiers
Kumar et al. A semantic machine learning algorithm for cyber threat detection and monitoring security
Alrefaai et al. Detecting phishing websites using machine learning
Golczynski et al. End-to-end anomaly detection for identifying malicious cyber behavior through NLP-based log embeddings
Saurabh et al. HMS-IDS: Threat Intelligence Integration for Zero-Day Exploits and Advanced Persistent Threats in IIoT
Jureček et al. Malware detection using a heterogeneous distance function
Nazarudeen et al. Efficient DDoS Attack Detection using Machine Learning Techniques
Rugangazi et al. Detecting Phishing Attacks Using Feature Importance-Based Machine Learning Approach
Yan Be sensitive to your errors: Chaining neyman-pearson criteria for automated malware classification
Rahman et al. Towards Developing Generative Adversarial Networks based Robust Intrusion Detection Systems for Imbalanced Dataset using Hadoop-PySpark
Khazaee et al. Using fuzzy c-means algorithm for improving intrusion detection performance