[go: up one dir, main page]

You et al., 2022 - Google Patents

sBiLSAN: Stacked bidirectional self-attention lstm network for anomaly detection and diagnosis from system logs

You et al., 2022

View PDF
Document ID
18277634030621302998
Author
You C
Wang Q
Sun C
Publication year
Publication venue
Intelligent Systems and Applications: Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 3

External Links

Snippet

High service availability is crucial for computer systems. Computer health diagnosis has become increasingly difficult due to a wide range of monitored information. Thus, it is essential to have the anomaly detection system along with firewalls and intrusion prevention …
Continue reading at www-leland.stanford.edu (PDF) (other versions)

Classifications

    • 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
    • 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
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/07Error detection; Error correction; Monitoring responding to the occurence of a fault, e.g. fault tolerance
    • 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
    • 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
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • 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
    • 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
    • G06F2201/00Indexing scheme relating to error detection, to error correction, and to monitoring

Similar Documents

Publication Publication Date Title
Wang et al. LightLog: A lightweight temporal convolutional network for log anomaly detection on the edge
Du et al. Lifelong anomaly detection through unlearning
Wang et al. Anomaly detection for industrial control system based on autoencoder neural network
Pan et al. Detecting web attacks with end-to-end deep learning
US11258814B2 (en) Methods and systems for using embedding from Natural Language Processing (NLP) for enhanced network analytics
Rehman et al. Evaluation of artificial intelligent techniques to secure information in enterprises
Elsayed et al. PredictDeep: security analytics as a service for anomaly detection and prediction
KR102359090B1 (en) Method and System for Real-time Abnormal Insider Event Detection on Enterprise Resource Planning System
Dou et al. Pc 2 a: predicting collective contextual anomalies via lstm with deep generative model
You et al. sBiLSAN: Stacked bidirectional self-attention lstm network for anomaly detection and diagnosis from system logs
Cai et al. A real-time trace-level root-cause diagnosis system in alibaba datacenters
WO2022115419A1 (en) Method of detecting an anomaly in a system
Wang et al. Maddc: Multi-scale anomaly detection, diagnosis and correction for discrete event logs
Goyal et al. R-caid: Embedding root cause analysis within provenance-based intrusion detection
US20250016185A1 (en) Apparatus and method for automatically analyzing malicious event log
Han et al. InterpretableSAD: Interpretable anomaly detection in sequential log data
Li et al. Glad: Content-aware dynamic graphs for log anomaly detection
Jose et al. Anomaly detection on system generated logs—a survey study
Lee et al. Advancing Autoencoder Architectures for Enhanced Anomaly Detection in Multivariate Industrial Time Series.
Khalkhali et al. Host-based web anomaly intrusion detection system, an artificial immune system approach
Hu et al. [Retracted] A Deep Spiking Neural Network Anomaly Detection Method
Chinnasamy Rank biserial stochastic feature embed bivariate kernelized regressive bootstrap aggregative classifier for school student dropout prediction
Xiao et al. Detecting anomalies in cluster system using hybrid deep learning model
Zhao Network security situational awareness and early warning architecture based on big data
Xin et al. Trustworthy AI-based Performance Diagnosis Systems for Cloud Applications: A Review