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Paper Abstract and Keywords
Presentation 2019-03-05 17:00
A Study on Automatic Generation of False Data Injection Attack against Connected Car Service Based on Reinforcement Learning
Yuichiro Dan, Keita Hasegawa, Takafumi Harada, Tomoaki Washio, Yoshihito Oshima (NTT) IBISML2018-109
Abstract (in Japanese) (See Japanese page) 
(in English) While the connected car is predicted to prevail by 2025, the appearance of novel cyber attacks is concerned. In this paper, we especially focus on the false data injection attack to such a service as collects information from the cars, analyzes the information, and drives the traffic society based on the result. The attack is such as follows: given a service which, for dynamic route selection, collects travel time from cars, calculates the data, and distributes the average travel time for each road, (1) malicious cars send false data to the service, (2) the service system calculates the wrong average travel time, (3) the system distributes the result, (4) the cars which believe the information select wrong routes, (5) finally, a traffic jam occurs. To examine the countermeasure technology of such unknown attack, the generation and analysis of the attack data are necessary. Furthermore, in order to reduce arbitrariness and cost in generating the data, the automatic generation is preferable to the manual one. Thus, in this paper, by using reinforcement learning, we developed a technique which automatically generates attack data inducing congestion on a vacant road.
Keyword (in Japanese) (See Japanese page) 
(in English) cyber security / connected car / vehicle to cloud to vehicle / false data injection attack / attack data generation / reinforcement learning / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 472, IBISML2018-109, pp. 31-38, March 2019.
Paper # IBISML2018-109 
Date of Issue 2019-02-26 (IBISML) 
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)
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Conference Information
Committee IBISML  
Conference Date 2019-03-05 - 2019-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) RIKEN AIP 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Machine learning, etc. 
Paper Information
Registration To IBISML 
Conference Code 2019-03-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Automatic Generation of False Data Injection Attack against Connected Car Service Based on Reinforcement Learning 
Sub Title (in English)  
Keyword(1) cyber security  
Keyword(2) connected car  
Keyword(3) vehicle to cloud to vehicle  
Keyword(4) false data injection attack  
Keyword(5) attack data generation  
Keyword(6) reinforcement learning  
1st Author's Name Yuichiro Dan  
1st Author's Affiliation NTT Secure Platform Laboratories (NTT)
2nd Author's Name Keita Hasegawa  
2nd Author's Affiliation NTT Secure Platform Laboratories (NTT)
3rd Author's Name Takafumi Harada  
3rd Author's Affiliation NTT Secure Platform Laboratories (NTT)
4th Author's Name Tomoaki Washio  
4th Author's Affiliation NTT Secure Platform Laboratories (NTT)
5th Author's Name Yoshihito Oshima  
5th Author's Affiliation NTT Secure Platform Laboratories (NTT)
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Date Time 2019-03-05 17:00:00 
Presentation Time 30 
Registration for IBISML 
Paper # IEICE-IBISML2018-109 
Volume (vol) IEICE-118 
Number (no) no.472 
Page pp.31-38 
#Pages IEICE-8 
Date of Issue IEICE-IBISML-2019-02-26 

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