[go: up one dir, main page]

Wang et al., 2008 - Google Patents

Processing of massive audit data streams for real-time anomaly intrusion detection

Wang et al., 2008

Document ID
11173169920693374188
Author
Wang W
Guan X
Zhang X
Publication year
Publication venue
Computer communications

External Links

Snippet

Intrusion detection is an important technique in the defense-in-depth network security framework. Most current intrusion detection models lack the ability to process massive audit data streams for real-time anomaly detection. In this paper, we present an effective anomaly …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3466—Performance evaluation by tracing or monitoring
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55—Detecting local intrusion or implementing counter-measures
    • G06F21/552—Detecting local intrusion or implementing counter-measures involving long-term monitoring or reporting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches

Similar Documents

Publication Publication Date Title
Wang et al. Processing of massive audit data streams for real-time anomaly intrusion detection
Wang et al. Locational detection of the false data injection attack in a smart grid: A multilabel classification approach
Maseer et al. Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
Wang et al. Profiling program behavior for anomaly intrusion detection based on the transition and frequency property of computer audit data
Devi et al. A Review Paper on IDS in Edge Computing or EoT
Zhao et al. A dimension reduction model and classifier for anomaly-based intrusion detection in internet of things
Beghdad Critical study of neural networks in detecting intrusions
US9275345B1 (en) System level user behavior biometrics using feature extraction and modeling
Saxena et al. Intrusion detection in KDD99 dataset using SVM-PSO and feature reduction with information gain
Wang et al. Attribute normalization in network intrusion detection
Wang et al. Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks
Wang et al. Identifying intrusions in computer networks with principal component analysis
Azad et al. Data mining in intrusion detection: a comparative study of methods, types and data sets
Abirami et al. Building an ensemble learning based algorithm for improving intrusion detection system
Fereidooni et al. Authentisense: A scalable behavioral biometrics authentication scheme using few-shot learning for mobile platforms
Cai et al. Mitigating behavioral variability for mouse dynamics: A dimensionality-reduction-based approach
Guan et al. Fast intrusion detection based on a non-negative matrix factorization model
CN111464529A (en) Network intrusion detection method and system based on cluster integration
Laamari et al. A hybrid bat based feature selection approach for intrusion detection
Devaraju et al. Performance analysis of intrusion detection system using various neural network classifiers
Soewu et al. Analysis of Data Mining-Based Approach for Intrusion Detection System
Wang et al. Intrusion detection using few-shot learning based on triplet graph convolutional network
Wang et al. Fcnn: An efficient intrusion detection method based on raw network traffic
Shen et al. Comparing classification algorithm for mouse dynamics based user identification
Medvedev et al. A decision-making framework for user authentication using keystroke dynamics