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

Xu et al., 2017 - Google Patents

A data-driven preprocessing scheme on anomaly detection in big data applications

Xu et al., 2017

Document ID
4834450409759566847
Author
Xu S
Qian Y
Hu R
Publication year
Publication venue
2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

External Links

Snippet

Efficient anomaly detection mechanisms are becoming an urgent and critical topic in the presence of big data applications. In this paper, we propose a data-driven preprocessing scheme on anomaly detection that incorporates a dimensionality reduction algorithm and …
Continue reading at ieeexplore.ieee.org (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
    • G06K9/6268Classification 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
    • 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
    • G06F17/30781Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F17/30784Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
    • 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
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
    • G06K9/00778Recognition or static of dynamic crowd images, e.g. recognition of crowd congestion
    • 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
    • G06K9/00221Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268Feature extraction; Face representation
    • G06K9/00281Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • 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
    • 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
    • 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
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models

Similar Documents

Publication Publication Date Title
Xu et al. A data-driven preprocessing scheme on anomaly detection in big data applications
Reddy et al. Using gaussian mixture models to detect outliers in seasonal univariate network traffic
US11663067B2 (en) Computerized high-speed anomaly detection
Li et al. FluxEV: a fast and effective unsupervised framework for time-series anomaly detection
US12124933B2 (en) Artificial intelligence system for anomaly detection in transaction data sets
CN113486334A (en) Network attack prediction method and device, electronic equipment and storage medium
US9225738B1 (en) Markov behavior scoring
US10713579B2 (en) Weighted similarity estimation in data streams with applications to collaborative filtering and viral marketing
Uddin et al. Online bad data detection using kernel density estimation
Rizvi et al. Detection of stock price manipulation using kernel based principal component analysis and multivariate density estimation
Wang et al. Online detection of abnormal events in video streams
Nguyen et al. Nested one-class support vector machines for network intrusion detection
Wang et al. Phishing scams detection via temporal graph attention network in Ethereum
Mansourifar et al. Hybrid cryptocurrency pump and dump detection
Panwar et al. An intrusion detection model for CICIDS-2017 dataset using machine learning algorithms
CN110659807A (en) Risk user identification method and device based on link
Singh et al. User behaviour based insider threat detection in critical infrastructures
Gulghane et al. A survey on intrusion detection system using machine learning algorithms
Khatibzadeh et al. Applying catastrophe theory for network anomaly detection in cloud computing traffic
Kulyadi et al. Anomaly detection using generative adversarial networks on firewall log message data
Orru et al. Detecting anomalies from video-sequences: a novel descriptor
Werner et al. Near real-time intrusion alert aggregation using concept-based learning
CN115330368A (en) Block chain abnormal transaction identification method and system integrating unsupervised machine learning
Mollaoğlu et al. Fraud detection on streaming customer behavior data with unsupervised learning methods
Jnanamurthy et al. Threat analysis and malicious user detection in reputation systems using mean bisector analysis and cosine similarity (MBACS)