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 |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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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IBISML2018-109 |
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) |
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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 |
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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 |
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NTT Secure Platform Laboratories (NTT) |
5th Author's Name |
Yoshihito Oshima |
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NTT Secure Platform Laboratories (NTT) |
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Speaker |
Author-1 |
Date Time |
2019-03-05 17:00:00 |
Presentation Time |
30 minutes |
Registration for |
IBISML |
Paper # |
IBISML2018-109 |
Volume (vol) |
vol.118 |
Number (no) |
no.472 |
Page |
pp.31-38 |
#Pages |
8 |
Date of Issue |
2019-02-26 (IBISML) |
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