疎構造学習およびグラフ畳み込みニューラルネットワークによる異常検知 / Anomaly detection by the method combined with sparse structure learn- ing and graph convolutional neural network

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- 24 89

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എܠ
໨త
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࣮ݧ݁Ռ
τϥϑΟοΫσʔλͷάϥϑԽ
৵ೖݕ஌͓ΑͼՄࢹԽ
·ͱΊ

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ਤ μʔΫωοτʹ͓͚Δ೥ؒ૯؍ଌύέοτ਺
ԯԯԯ
ԯ
ԯ
ԯ
ԯ
ԯ
ԯ
ԯ
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·͖͍ͬͯͯΔɽ

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α Π ό ʔ ߈ ܸ ର ࡦ ͷ ̍ ͭ ͱ ͠ ͯ ɼ ෆ ਖ਼ ͳ ௨ ৴ Λ ݕ ஌ ͢ Δ
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ҟৗݕ஌
τϥϑΟοΫ ݕূ ରॲ
ͲΜͳҟৗʁ
ຊ౰ʹҟৗʁ
ਖ਼ৗҟৗ
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χϡʔϥϧωοτϫʔΫ ਖ਼ৗҟৗ

αϙʔτϕΫλʔϚγϯ ਖ਼ৗҟৗ

-45. ҟৗͷछྨʢछʣ

ϕΠδΞϯωοτϫʔΫ ҟৗͷछྨʢछʣ

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ఏڙ͕ඞཁͰ͋Δɽ

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ը૾ॲཧͷ෼໺Ͱ͸ɼೖྗը૾ͷͲͷ෦෼͕ॏཁͰ͋Δ͔Λఆྔత਺஋͓Αͼ
ͦΕʹج͍ͮͨՄࢹԽʹΑͬͯ൑ఆ݁ՌΛઆ໌͢Δख๏͕͢ͰʹఏҊ͞Ε͍ͯΔ
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ը૾ॲཧͷ෼໺Ͱ͸ɼೖྗը૾ͷͲͷ෦෼͕ॏཁͰ͋Δ͔Λఆྔత਺஋͓Αͼ
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τϥϑΟοΫͷͲͷཁૉ͕ݕ஌݁Ռʹରͯ͠Өڹ͍͔ͯͨ͠ Λ
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DARPA 1998 Dataset

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ΤοδɿϑΟʔϧυ৘ใͷ࣌ܥྻతڍಈͷ૬ؔ
άϥϑߏ଄Խ

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എܠ
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࣮ݧ݁Ռ
·ͱΊ

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ՄࢹԽ
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ෳ਺ͷ࣌ܥྻಛ௃ྔΛநग़
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ػցֶशख๏

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ि ༵೔ ߈໊ܸ ࣌ؒ
݄ GPSNBU
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छྨͷ࣌ܥྻಛ௃ྔʹ෼ղ
ର਺ࠩ෼
෼ࠩ෼

ՄࢹԽ
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ඪ४Խ
dڭࢣ͋Γֶश d
৵ೖݕ஌

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ʜ ʜ

΢Οϯυ΢αΠζ෼
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๏Ͱ͋Δ(SBQIJDBM-BTTPΛར༻͠ɼ෼ͷ
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ՄࢹԽ
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ඪ४Խ
dڭࢣ͋Γֶश d
৵ೖݕ஌

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ʜ ʜ
΢Οϯυ΢αΠζ෼

ग़ྗ:
ʢਖ਼ৗҟৗʣ
෼ྨ

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σʔλͷׂ߹ʢ܇࿅ɿݕূʣɿ70:30
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ඪ४Խ
dڭࢣ͋Γֶश d
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৵ೖݕ஌

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άϥϑ৞ΈࠐΈχϡʔϥϧωοτϫʔΫʢ($//ʣ

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ਤ άϥϑ৞ΈࠐΈχϡʔϥϧωοτϫʔΫͷུ֓ਤ͓Αͼάϥϑදݱ
ਤ ৞ΈࠐΈԋࢉͷྫ͓Αͼάϥϑදݱ

ग़ྗ:
ʢਖ਼ৗҟৗʣ
෼ྨ

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I
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I

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%BWJE%VWFOBVE FUBM *OUIF1SPD/*14 .POUSFBM $BOBEB %FDFNFCFS
ຊݚڀͰ͸ɼ($//ͷதͰ΋/'1 /FVSBM 'JOHFS 1SJOUΛར༻͢Δɽઌߦݚڀ
Ͱ͸ɼಟੑͳͲͷߴਫ਼౓ͳ༧ଌʹ੒ޭ͠ɼ'JOHFS 1SJOUͷੜ੒ʹ੒ޭͨ͠ɽ
'JOHFS 1SJOU͸ɼೖྗͨ͠άϥϑߏ଄Λ࣍ݩϕΫτϧͰදݱͨ͠΋ͷͰ͋Δɽ
֤Ϗοτ͕෦෼άϥϑʹ૬౰͠ɼ஋͕݁Ռʢಟੑʣʹର͢ΔӨڹ౓ ʹ૬౰͢Δɽ
ਤ ಟੑΛ༧ଌ͢ΔͨΊʹ࠷దԽ͞Εͨ'JOHFS1SJOUͷՄࢹԽ

ग़ྗ:
ʢਖ਼ৗҟৗʣ
෼ྨ

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%BWJE%VWFOBVE FUBM *OUIF1SPD/*14 .POUSFBM $BOBEB %FDFNFCFS
ຊݚڀͰ͸ɼ($//ͷதͰ΋/'1 /FVSBM 'JOHFS 1SJOUΛར༻͢Δɽઌߦݚڀ
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'JOHFS 1SJOU͸ɼೖྗͨ͠άϥϑߏ଄Λ࣍ݩϕΫτϧͰදݱͨ͠΋ͷͰ͋Δɽ
֤Ϗοτ͕෦෼άϥϑʹ૬౰͠ɼ஋͕݁Ռʢಟੑʣʹର͢ΔӨڹ౓ ʹ૬౰͢Δɽ
ਤ ಟੑΛ༧ଌ͢ΔͨΊʹ࠷దԽ͞Εͨ'JOHFS1SJOUͷՄࢹԽ

ग़ྗ:
ʢਖ਼ৗҟৗʣ
෼ྨ

1PPMJOH
'JOHFSQSJOU
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̍ۙ๣ ۙ๣
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ʜ ʜ
΢Οϯυ΢αΠζ෼

ग़ྗ:
ʢਖ਼ৗҟৗʣ
෼ྨ

1PPMJOH
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ΤϙοΫ਺ɿ
σʔλͷׂ߹ʢ܇࿅ɿݕূʣɿ70:30
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ՄࢹԽ
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ඪ४Խ
dڭࢣ͋Γֶश d
৵ೖݕ஌

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എܠ
໨త
ఏҊख๏
࣮ݧ݁Ռ
·ͱΊ

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छྨͷ࣌ܥྻಛ௃ྔʹ- ੍໿෇͖ͷૄߏ଄ֶशख๏(SBQIJDBM -BTTPΛద
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ૄͳάϥϑߏ଄ʹ͢Δ͜ͱʹΑΓɼ৘ใྔͷѹॖ΍ϊΠζ΁ͷؤڧੑʹ༗ޮͰ
͋Δͱߟ͑ΒΕΔɽ
(SBQIJDBM-BTTP
ਤ τϥϑΟοΫσʔλ͔Β࡞੒ͨ͠άϥϑߏ଄(SBQIJDBM-BTTPͷద༻લ͓Αͼ ద༻ޙ

View Slide

എܠ
໨త
ఏҊख๏
࣮ݧ݁Ռ
·ͱΊ

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ਖ਼ղσʔλ
༧ଌ݁Ռ
άϥϑߏ଄Խͨ͠τϥϑΟοΫσʔλΛ($//Ͱֶशͨ݁͠Ռɼ༧ଌਫ਼౓͕
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ਤ ਖ਼ղσʔλ͓ΑͼֶशϞσϧʹΑΔ༧ଌ݁Ռ
ख๏ ༧ଌਫ਼౓ จݙ
χϡʔϥϧωοτϫʔΫ

αϙʔτϕΫλʔϚγϯ

-45.

ϕΠδΞϯωοτϫʔΫ

ද ػցֶशܕ*%4ͷઌߦݚڀͷྫ

4.VLLBNBMB FUBM 5SBJOJOH

+,JNFUBM ``JO1SPD*OU$POG1MBUGPSN5FDIOPM4FSWJDF
r

4$IFCSPMV FUBM $PNQVUFST4FDVSJUZ

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($//Ͱֶशͨ͠ϞσϧΛར༻͠ɼ'JOHFS 1SJOUͷऔಘʹ੒ޭͨ͠ɽ
4:/GMPPE߈ܸ࣌ɼҟৗ͕ݕ஌͞Εɼ'JOHFS 1SJOU಺Ͱߴ͍Өڹ౓Λࣔ͢෦
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(b) ਤ 'JOHFSQSJOU͓ΑͼҟৗͷཁҼͱͳͬͨ෦෼άϥϑͷҰྫ4:/qPPE߈ܸ
෦෼άϥϑ
'JOHFS1SJOU
Өڹ౓

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4NVSG߈ܸ࣌ɼ'JOHFS1SJOU಺ͷӨڹ౓ͷߴ͍෦෼άϥϑ͸ɼૹ৴ݩ*1͓Αͼ
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疎構造学習およびグラフ畳み込みニューラルネットワークによる異常検知 / Anomaly detection by the method combined with sparse structure learn- ing and graph convolutional neural network

疎構造学習およびグラフ畳み込みニューラルネットワークによる異常検知 / Anomaly detection by the method combined with sparse structure learn- ing and graph convolutional neural network

kumagallium

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疎構造学習およびグラフ畳み込みニューラルネットワーク による異常検知 / Anomaly detection by the method combined with sparse structure learn- ing and graph convolutional neural network

疎構造学習およびグラフ畳み込みニューラルネットワーク による異常検知 / Anomaly detection by the method combined with sparse structure learn- ing and graph convolutional neural network

kumagallium

More Decks by kumagallium

Other Decks in Research

Featured

Transcript

疎構造学習およびグラフ畳み込みニューラルネットワークによる異常検知 / Anomaly detection by the method combined with sparse structure learn- ing and graph convolutional neural network

疎構造学習およびグラフ畳み込みニューラルネットワークによる異常検知 / Anomaly detection by the method combined with sparse structure learn- ing and graph convolutional neural network