| Paper Abstract and Keywords |
| Presentation |
2021-03-01 14:55
Dynamic Analysis of Persistent IoT Malware UsingAdaptive Sandbox Takahiro Inoue (YNU), Satoshi Hara (YNU/FUJISOFT), Hironobu Sakaki, Kouichirou Okada (YNU/RainForest), Eitaro Shioji, Mitsuaki Akiyama (NTT), Takayuki Sasaki, Rui Tanabe, Katsunari Yoshioka, Koji Nakao, Tsutomu Matsumoto (YNU) ICSS2020-41 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Malware that infects vulnerable IoT devices is becoming more sophisticated. Unlike legacy IoT malware, cases of persistent IoT malware that continues to infect devices even after their reboot has been reported. Since such malware depends on the configuration of a specific device, it is assumed that the behavior cannot be observed correctly by dynamic analysis using a virtual environment based on a general embedded OS. In this study, we propose a method to estimate the configuration of the target IoT devices by analyzing system calls executed by the malware and to adapt the sandbox to the environment in which the malware can work. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Embedded System / IoT Malware / Persistent Infection / Dynamic Analysis / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 120, no. 384, ICSS2020-41, pp. 90-95, March 2021. |
| Paper # |
ICSS2020-41 |
| Date of Issue |
2021-02-22 (ICSS) |
| ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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| Download PDF |
ICSS2020-41 |