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| Paper Abstract and Keywords | ||
| Presentation | 2024-03-12 16:00 Improvement of Unknown Malicious Domain Detection Based on DNS Query History Analysis Hiroto Yamada, Daiki Nobayashi, Takeshi Ikenaga (kyutech)  SITE2023-83 IA2023-89 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Network users are increasing and there is concern about the malware infection. In some cases, malware-infected terminals use Domain Name System (DNS) when communicating with command and control (C&C) servers to obtain information for attacks. In previous study, a method to detect unknown malicious domains was proposed by focusing on the DNS logs access history of malware-infected terminals and deriving co-occurrence relationships with known malicious domains based on the assumption that characteristic behaviors appear before and after accesses with the C&C server. However, there is a problem that the detection accuracy of unknown malicious domains decreases when the training data is small. In this paper aims to improve the accuracy of malicious domain detection by also focusing on record and time information from DNS log responses. In this study, evaluates the effectiveness of the proposed method in terms of malicious domain detection accuracy, using actual DNS logs. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | DNS / Machine Learning / malware / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 422, IA2023-89, pp. 92-97, March 2024. | |
| Paper # | IA2023-89 | |
| Date of Issue | 2024-03-05 (SITE, IA) | |
| 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) | |
| Download PDF | SITE2023-83 IA2023-89 |
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| Conference Information | |
| Committee | IA SITE IPSJ-IOT |
| Conference Date | 2024-03-12 - 2024-03-14 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Miyakojima City Future Creation Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Internet and Information Ethics Education, etc. |
| Paper Information | |
| Registration To | IA |
| Conference Code | 2024-03-IA-SITE-IOT |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Improvement of Unknown Malicious Domain Detection Based on DNS Query History Analysis |
| Sub Title (in English) | |
| Keyword(1) | DNS |
| Keyword(2) | Machine Learning |
| Keyword(3) | malware |
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| 1st Author's Name | Hiroto Yamada |
| 1st Author's Affiliation | Kyushu Institute of Technology (kyutech) |
| 2nd Author's Name | Daiki Nobayashi |
| 2nd Author's Affiliation | Kyushu Institute of Technology (kyutech) |
| 3rd Author's Name | Takeshi Ikenaga |
| 3rd Author's Affiliation | Kyushu Institute of Technology (kyutech) |
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| Speaker | Author-1 |
| Date Time | 2024-03-12 16:00:00 |
| Presentation Time | 25 minutes |
| Registration for | IA |
| Paper # | SITE2023-83, IA2023-89 |
| Volume (vol) | vol.123 |
| Number (no) | no.421(SITE), no.422(IA) |
| Page | pp.92-97 |
| #Pages | 6 |
| Date of Issue | 2024-03-05 (SITE, IA) |
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