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Paper Abstract and Keywords
Presentation 2017-03-14 11:20
Graph based Detection of Advanced Persistent Threat on LAN
Hiroki Nagayama, Bo Hu, Takaaki Koyama, Jun Miyoshi (NTT) ICSS2016-65
Abstract (in Japanese) (See Japanese page) 
(in English) Recently the countermeasures against continuously increasing Advanced Persistent Threats(APT) are urgently necessary.
In APT, the attacker remotely controls the infected enterprise host and operate stealthily for network reconnaissance, further intrusion on others and data exfiltration.
It is difficult to prevent APT during initial intrusion phase because attackers usually apply unknown malwares. Therefore, it is important to detect attackers' reconnaissance activities and specify infected hosts in early stage accepting the possibility of initial intrusion.
Most of conventional techniques for APT detection require data from packet capture and network flow, and not reliable enough due to setup operation cost, huge traffic volume and so on.
Therefore, we focus on ARP request traffic which can be obtained more easily and has small traffic volume.
Conventional methods using ARP traffic only can detect reconnaissance activities that have distinctive features such as connecting to
a large number of destinations, to a destination with high frequency or to a unused IP address.
However, in the case of APT, due to stealthy operation of the attacker, it is difficult to extract required features for applying those method.
In our research, we propose an anomaly detection method which 1) represents observed communication between hosts as a graph by using ARP request traffic, 2) extracts normal pattern between different hosts as a set of sub-graphs, 3) and detect unknown traffic across different sub-graphs as anomaly pattern.
The proposed method realizes detection of reconnaissance activities of APT in early stage.
Keyword (in Japanese) (See Japanese page) 
(in English) advanced persistent threat / reconnaissance activities / ARP / graph mining / anomaly detection / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 522, ICSS2016-65, pp. 153-158, March 2017.
Paper # ICSS2016-65 
Date of Issue 2017-03-06 (ICSS) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee ICSS IPSJ-SPT  
Conference Date 2017-03-13 - 2017-03-14 
Place (in Japanese) (See Japanese page) 
Place (in English) University of Nagasaki 
Topics (in Japanese) (See Japanese page) 
Topics (in English) System Security, etc. 
Paper Information
Registration To ICSS 
Conference Code 2017-03-ICSS-SPT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Graph based Detection of Advanced Persistent Threat on LAN 
Sub Title (in English)  
Keyword(1) advanced persistent threat  
Keyword(2) reconnaissance activities  
Keyword(3) ARP  
Keyword(4) graph mining  
Keyword(5) anomaly detection  
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1st Author's Name Hiroki Nagayama  
1st Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
2nd Author's Name Bo Hu  
2nd Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
3rd Author's Name Takaaki Koyama  
3rd Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
4th Author's Name Jun Miyoshi  
4th Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
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Speaker Author-1 
Date Time 2017-03-14 11:20:00 
Presentation Time 25 minutes 
Registration for ICSS 
Paper # ICSS2016-65 
Volume (vol) vol.116 
Number (no) no.522 
Page pp.153-158 
#Pages
Date of Issue 2017-03-06 (ICSS) 


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