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Analysis of Android Applications Shared on Twitter Focusing on Accessibility Services
https://ipsj.ixsq.nii.ac.jp/records/220193
https://ipsj.ixsq.nii.ac.jp/records/220193e9c42632-0a52-401e-9ca1-87a6c01d5eb6
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IPSJ-JNL6309009.pdf (1.0 MB)
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Copyright (c) 2022 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | Journal(1) | |||||||||||||||
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| 公開日 | 2022-09-15 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | Analysis of Android Applications Shared on Twitter Focusing on Accessibility Services | |||||||||||||||
| タイトル | ||||||||||||||||
| 言語 | en | |||||||||||||||
| タイトル | Analysis of Android Applications Shared on Twitter Focusing on Accessibility Services | |||||||||||||||
| 言語 | ||||||||||||||||
| 言語 | eng | |||||||||||||||
| キーワード | ||||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | [特集:量子時代をみすえたコンピュータセキュリティ技術] accessibility service, Android app, malware, social networking services | |||||||||||||||
| 資源タイプ | ||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||
| 資源タイプ | journal article | |||||||||||||||
| 著者所属 | ||||||||||||||||
| Graduate School of Natural Science and Technology, Okayama University | ||||||||||||||||
| 著者所属 | ||||||||||||||||
| Graduate School of Natural Science and Technology, Okayama University／Engineering School of Grenoble INP group - Esisar | ||||||||||||||||
| 著者所属 | ||||||||||||||||
| SecureBrain Corporation | ||||||||||||||||
| 著者所属 | ||||||||||||||||
| SecureBrain Corporation | ||||||||||||||||
| 著者所属 | ||||||||||||||||
| Faculty of Natural Science and Technology, Okayama University | ||||||||||||||||
| 著者所属(英) | ||||||||||||||||
| en | ||||||||||||||||
| Graduate School of Natural Science and Technology, Okayama University | ||||||||||||||||
| 著者所属(英) | ||||||||||||||||
| en | ||||||||||||||||
| Graduate School of Natural Science and Technology, Okayama University / Engineering School of Grenoble INP group - Esisar | ||||||||||||||||
| 著者所属(英) | ||||||||||||||||
| en | ||||||||||||||||
| SecureBrain Corporation | ||||||||||||||||
| 著者所属(英) | ||||||||||||||||
| en | ||||||||||||||||
| SecureBrain Corporation | ||||||||||||||||
| 著者所属(英) | ||||||||||||||||
| en | ||||||||||||||||
| Faculty of Natural Science and Technology, Okayama University | ||||||||||||||||
| 著者名 |
Shuichi, Ichioka
× Shuichi, Ichioka
× Estelle, Pouget
× Takao, Mimura
× Jun, Nakajima
× Toshihiro, Yamauchi
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| 著者名(英) |
Shuichi, Ichioka
× Shuichi, Ichioka
× Estelle, Pouget
× Takao, Mimura
× Jun, Nakajima
× Toshihiro, Yamauchi
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| 論文抄録 | ||||||||||||||||
| 内容記述タイプ | Other | |||||||||||||||
| 内容記述 | As the use of mobile devices for financial payments continues to increase, prevention of attacks by Android malware becomes critical. In this study, we collected apps shared on Twitter in 2018 to create a Twitter shared apps dataset. We also clarified the proportion of apps that contained malware and those utilizing accessibility services (ASs). Furthermore, we faced issues in determining whether an app is suspicious or benign using VirusTotal results and extracting permissions from apps. Using VirusTotal, we studied the distribution of the number of apps for each anti-virus engine that “detected” malware and analyzed the changes in results over time to determine thresholds. Additionally, we examined methods for extracting permissions using Apktool and the aapt command, installed apps that were judged to request ASs and examined whether they were requested to obtain more accurate results. We analyzed the usage rate of ASs and the requested permissions. Furthermore, we analyzed the target Android application program interface levels of suspicious apps that use ASs. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.30(2022) (online) DOI http://dx.doi.org/10.2197/ipsjjip.30.601 ------------------------------ |
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| 論文抄録(英) | ||||||||||||||||
| 内容記述タイプ | Other | |||||||||||||||
| 内容記述 | As the use of mobile devices for financial payments continues to increase, prevention of attacks by Android malware becomes critical. In this study, we collected apps shared on Twitter in 2018 to create a Twitter shared apps dataset. We also clarified the proportion of apps that contained malware and those utilizing accessibility services (ASs). Furthermore, we faced issues in determining whether an app is suspicious or benign using VirusTotal results and extracting permissions from apps. Using VirusTotal, we studied the distribution of the number of apps for each anti-virus engine that “detected” malware and analyzed the changes in results over time to determine thresholds. Additionally, we examined methods for extracting permissions using Apktool and the aapt command, installed apps that were judged to request ASs and examined whether they were requested to obtain more accurate results. We analyzed the usage rate of ASs and the requested permissions. Furthermore, we analyzed the target Android application program interface levels of suspicious apps that use ASs. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.30(2022) (online) DOI http://dx.doi.org/10.2197/ipsjjip.30.601 ------------------------------ |
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| 書誌レコードID | ||||||||||||||||
| 収録物識別子タイプ | NCID | |||||||||||||||
| 収録物識別子 | AN00116647 | |||||||||||||||
| 書誌情報 |
情報処理学会論文誌 巻 63, 号 9, 発行日 2022-09-15 |
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| ISSN | ||||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||||
| 収録物識別子 | 1882-7764 | |||||||||||||||
| 公開者 | ||||||||||||||||
| 言語 | ja | |||||||||||||||
| 出版者 | 情報処理学会 | |||||||||||||||
