CA2421928A1 - Anomaly detection system and a method of teaching it - Google Patents

Anomaly detection system and a method of teaching it Download PDF

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Publication number
CA2421928A1
CA2421928A1 CA002421928A CA2421928A CA2421928A1 CA 2421928 A1 CA2421928 A1 CA 2421928A1 CA 002421928 A CA002421928 A CA 002421928A CA 2421928 A CA2421928 A CA 2421928A CA 2421928 A1 CA2421928 A1 CA 2421928A1
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input data
time
indicators
period
learning mechanism
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CA2421928C (en
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Albert Hoglund
Kimmo Hatonen
Antti Sorvari
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Nokia Solutions and Networks Oy
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/243—Classification techniques relating to the number of classes
    • G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Mathematical Physics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Evolutionary Biology (AREA)
  • Computational Linguistics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)
  • Alarm Systems (AREA)
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  • Debugging And Monitoring (AREA)
  • General Factory Administration (AREA)

Abstract

A method for teaching an anomaly detecting mechanism in a system comprising observable elements (302), at least one of which has a periodic time-dependent behaviour, the anomaly detecting mechanism comprising a computerized learning mechanism (314). The method comprises assembling indicators (304) indicating the behaviour of the elements (302) and arranging the assembled indicators such that each observable element's indicators are assigned to the same input data component. The learning mechanism (314) is taught so that the input data of the learning mechanism comprises the input data components which are based on the assembled indicators (304). Points which approximate the input data are placed in the input space. A presentation of time (420 - 424) is incorporated into at least one input data component wherein the presentation of time is periodic, continuous and unambiguous within the period of the at least one element with periodic time-dependent behaviour.

Claims (10)

1. A method for teaching an anomaly detecting mechanism in a sys-tem comprising observable elements (302), at least one of which has a peri-odic time-dependent behaviour, the anomaly detecting mechanism comprising a computerized learning mechanism (314) having an input space for defining input data consisting of input data components (11, 12);
the method comprising:
assembling indicators (304) indicating the behaviour of the observ-able elements (302) and arranging the assembled indicators such that each observable element's indicators are assigned to the same input data compo-nent;
teaching the learning mechanism (314) such that the input data of the learning mechanism comprises the input data components which are based on the assembled indicators (304); and placing points (14) which approximate the input data in the input space;
characterized by:
incorporating a presentation of time (420 - 424) into at least one in-put data component (11, 12);
wherein the presentation of time (420 - 424) is periodic, continuous and unambiguous within the period (L) of the at least one element with peri-odic time-dependent behaviour.
2. A method according to claim 1, characterized in that the learning mechanism is or comprises a self-organizing map.
3. A method according to claim 1 or 2, characterized in that the presentation of time has a first period and at least one second period which is a multiple of the first period.
4. A method according to any one of the preceding claims, char-acterized by scaling the input data components such that each has the same variance, preferably one.
5. A method according to any one of the preceding claims, char-acterized in that the presentation of time has a variable resolution such that one bit corresponds to different units of time depending on the changes in the time-dependent behaviour.
6. An arrangement for detecting anomalies in a system comprising observable elements (302), at least one of which has a periodic time-dependent behaviour;
the arrangement comprising:
a computerized learning mechanism (314) having an input space for defining input data consisting of input data components (11, 12);
means for assembling indicators (304) indicating the behaviour of the observable elements (302) and arranging the assembled indicators such that each observable element's indicators are assigned to the same input data component;
means for teaching the learning mechanism (314) such that the in-put data of the learning mechanism comprises the input data components which are based on the assembled indicators (304);
means for placing points (14) which approximate the input data in the input space;
the arrangement characterized by:
at least one input data component (11, 12) comprising a presenta-tion of time (420 - 424);
wherein the presentation of time (420 - 424) is periodic, continuous and unambiguous within the period (L) of the at least one element with peri-odic time-dependent behaviour.
7. An arrangement according to claim 6, characterized in that the learning mechanism is or comprises a self-organizing map.
8. An arrangement according to claim 6 or 7, characterized in that the presentation of time has a first period and at least one second period which is a multiple of the first period.
9. An arrangement according to any one of claims 6 - 8, charac-terized by being comprised in a single network element.
10. A computer readable storage medium comprising software for a computer, characterized in that executing the software in the computer causes the computer to carry out the method steps of claim 1.
CA2421928A 2000-09-11 2001-09-10 Anomaly detection system and a method of teaching it Expired - Fee Related CA2421928C (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
FI20001997A FI114749B (en) 2000-09-11 2000-09-11 Anomaly detection system and method for teaching it
FI20001997 2000-09-11
PCT/FI2001/000783 WO2002021242A1 (en) 2000-09-11 2001-09-10 Anomaly detection system and a method of teaching it

Publications (2)

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CA2421928A1 true CA2421928A1 (en) 2002-03-14
CA2421928C CA2421928C (en) 2011-11-15

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CA2421928A Expired - Fee Related CA2421928C (en) 2000-09-11 2001-09-10 Anomaly detection system and a method of teaching it

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US (2) US7519860B2 (en)
EP (2) EP1325588A1 (en)
JP (1) JP4436042B2 (en)
CN (1) CN1196984C (en)
AU (2) AU2001269056A1 (en)
CA (1) CA2421928C (en)
FI (1) FI114749B (en)
WO (2) WO2002021774A1 (en)

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CN1455890A (en) 2003-11-12
CN1196984C (en) 2005-04-13
AU2001287759A1 (en) 2002-03-22
CA2421928C (en) 2011-11-15
US20030225520A1 (en) 2003-12-04
AU2001269056A1 (en) 2002-03-22
JP4436042B2 (en) 2010-03-24
FI114749B (en) 2004-12-15
EP1334417A1 (en) 2003-08-13
US7519860B2 (en) 2009-04-14
WO2002021774A1 (en) 2002-03-14
FI20001997A (en) 2002-03-12
EP1325588A1 (en) 2003-07-09
WO2002021242A1 (en) 2002-03-14
JP2004508631A (en) 2004-03-18
FI20001997A0 (en) 2000-09-11
US20040039968A1 (en) 2004-02-26
US7613668B2 (en) 2009-11-03

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