IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2020-03-06 10:30
A Consideration on Efficient Anomaly Detection Based on Isolation Forest
Tsubasa Ikeda, Shinobu Nagayama, Masato Inagi, Shin'ichi Wakabayashi (HCU) VLD2019-125 HWS2019-98
Abstract (in Japanese) (See Japanese page) 
(in English) Isolation Forest is a method to detect anomalies by ensemble learning of binary decision trees. It traverses each decision tree according to the input data, and determines that the data is normal if its path length is longer than a threshold, otherwise it is anomaly. In this method, computation time needed for decision of normal data gets longer than necessary. In this study, we use a multi-valued decision tree based Isolation Forest in which the number of branches at each node in decision trees is more than 2, and try to shorten overall path length. Through experiments, we investigate relations of the number of branches with, path length, discrimination time, total number of branches, and detection accuracy to show the effectiveness of the Isolation Forest using multi-valued decision trees. We also consider that it is possible to know useful attributes for detecting anomaly data by checking the attributes frequently selected at each node of each decision tree when anomaly data is detected. We investigate by experiment and consider attribute analysis of anomaly data.
Keyword (in Japanese) (See Japanese page) 
(in English) Anomaly Detection / Isolation Forest / Multi-Valued Decision Trees / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 443, VLD2019-125, pp. 179-184, March 2020.
Paper # VLD2019-125 
Date of Issue 2020-02-26 (VLD, HWS) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF VLD2019-125 HWS2019-98

Conference Information
Committee HWS VLD  
Conference Date 2020-03-04 - 2020-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Ken Seinen Kaikan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Design Technology for System-on-Silicon, Hardware Security, etc. 
Paper Information
Registration To VLD 
Conference Code 2020-03-HWS-VLD 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Consideration on Efficient Anomaly Detection Based on Isolation Forest 
Sub Title (in English)  
Keyword(1) Anomaly Detection  
Keyword(2) Isolation Forest  
Keyword(3) Multi-Valued Decision Trees  
1st Author's Name Tsubasa Ikeda  
1st Author's Affiliation Hiroshima City University (HCU)
2nd Author's Name Shinobu Nagayama  
2nd Author's Affiliation Hiroshima City University (HCU)
3rd Author's Name Masato Inagi  
3rd Author's Affiliation Hiroshima City University (HCU)
4th Author's Name Shin'ichi Wakabayashi  
4th Author's Affiliation Hiroshima City University (HCU)
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Speaker Author-1 
Date Time 2020-03-06 10:30:00 
Presentation Time 25 minutes 
Registration for VLD 
Paper # VLD2019-125, HWS2019-98 
Volume (vol) vol.119 
Number (no) no.443(VLD), no.444(HWS) 
Page pp.179-184 
Date of Issue 2020-02-26 (VLD, HWS) 

[Return to Top Page]

[Return to IEICE Web Page]

The Institute of Electronics, Information and Communication Engineers (IEICE), Japan