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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 洪士灝(Shih-Hao Hung) | |
| dc.contributor.author | Shih-Jie Chang | en |
| dc.contributor.author | 張世杰 | zh_TW |
| dc.date.accessioned | 2021-06-16T08:47:07Z | - |
| dc.date.available | 2018-08-26 | |
| dc.date.copyright | 2013-08-26 | |
| dc.date.issued | 2013 | |
| dc.date.submitted | 2013-08-20 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59054 | - |
| dc.description.abstract | 由於現代的行動裝置越來越普及，功能也越來越強大，其中所隱含的個人隱私資料也越來越龐大，這些隱私資料不只是使用者的個人資料，也包含這台裝置上的感應器收集到的資訊，如GPS位置等等。但是在行動裝置擁有越來越大量隱私資料的同時，也讓這些私密資料被洩漏出去的風險越來越高，不論是不小心的還是惡意的洩漏。
Google 開發的 Android 作業系統提供了一套基於權限的安全機制來限制應用程式無法隨意存取使用者的私密資料，然而這套機制卻不夠縝密導致許多惡意程式仍然可以逃過此機制。為了解決這個問題，我們提出了一套結合了聰明的事件產生器與動態分析工具的自動化偵測環境，名為Ape，是一套能夠自動偵測 Android 應用程式是否會洩漏敏感資料的服務。利用 Ape，使用者可以事先檢查任何一個從第三方網站下載的應用程式，並且得到一份分析報告包含資料是否洩漏以及一個特定的 Activity Call Graph (ACG)， 供使用者做進一步的分析。 為了分析 Ape 的效能，我們從數個 Android 第三方網站中總計下載了 500 個應用程式。我們和 Android Monkey 做比較，發現在惡意程式類別中 Ape 偵測到 86 個程式洩漏資料，而 Android Monkey 最多也只能偵測到 31 個資料洩漏。在時間的比較上，Ape 平均一次測試需要 1983 秒，效率遠比 Android Monkey 的隨機點擊還高。 | zh_TW |
| dc.description.abstract | As mobile devices become more widespread and powerful, many of them store sensitive data, and personal information, as well as sense the surrounding environment. Those mobile applications which have access to the storage and sensors may leak sensitive data maliciously.
While the Android system provides a permissions-based security model to protect against such malware, the security model is too coarse-grained and does not work well in practice. To help detect malware, we propose a smart automatic testing environment, called Ape, a service which combines a smart input generator and a dynamic taint analysis tool for automatically finding data leaks of sensitive information in Android applications. With Ape, user can inspect an application before using it, and get a data leakage report with specific Activity Call Graph (ACG) for further analysis. In this thesis work, we evaluate the efficacy of Ape by testing 500 Android applications downloaded from several Android markets. Compared with Android Monkey, Ape quickly found that 86 applications have leaked private data while Android Monkey only detected 31 applications in its best effort. On average, Ape can complete a test in 1983 seconds, which is much more efficient than the Android Monkey's random clicking. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T08:47:07Z (GMT). No. of bitstreams: 1 ntu-102-R00922094-1.pdf: 3017448 bytes, checksum: 5a0900b434e634f0933a9142ca162afc (MD5) Previous issue date: 2013 | en |
| dc.description.tableofcontents | Acknowledgments . . . . . . i
中文摘要 . . . . . ii Abstract. . . . . iii 1 Introduction . .1 1.1Thesis Organization . . . . . . .. . . 2 2 Related Work .. ... . . . . . . . . 3 3 Background . . . .. . 5 3.1 Activity and Lifecycle. . . .5 3.2 Java Native Interface(JNI) . . . . . . . . . 6 3.3 . Android Monkey . . . . . . 9 4 Framework and Implementation . . . . . . . . 10 4.1 Taintdroid . . . 10 4.2 Input generator . . . . 11 4.3 Activity Call Graph. . . . . . . 12 4.3.1 Implementation . . . . . . . . . . . . 13 4.3.2 Limitation. . . . . 13 4.3.3 Solution . . . . 14 5 Experimental Results. . . .16 5.1 Single Malware Analysis .. . . . . . 17 5.2 Category Analysis. . . . . . . . . .. . . . . . 19 5.3 Time Consuming Analysis . . . .. . . . . . . . 23 5.4 Combination with Android Monkey . . . . . . . . 23 6 Future Work . . . . 26 7 Conclusion . . . . . . 28 Bibliography . . . . 29 | |
| dc.language.iso | en | |
| dc.subject | 雲端服務 | zh_TW |
| dc.subject | 惡意程式 | zh_TW |
| dc.subject | 資料洩漏 | zh_TW |
| dc.subject | 自動化測試 | zh_TW |
| dc.subject | 智慧型手機 | zh_TW |
| dc.subject | automatic testing | en |
| dc.subject | malware | en |
| dc.subject | data leakage | en |
| dc.subject | Cloud Service | en |
| dc.subject | Smartphone | en |
| dc.title | Ape: Android系統惡意程式之自動化測試環境 | zh_TW |
| dc.title | Ape: A Smart Automatic Testing Environment for Android Malware | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 101-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 廖世偉(Shih-Wei Liao),鍾葉青(Yeh-Ching Chung),徐慰中(Wei-Chung Hsu) | |
| dc.subject.keyword | 惡意程式,資料洩漏,自動化測試,智慧型手機,雲端服務, | zh_TW |
| dc.subject.keyword | malware,data leakage,automatic testing,Smartphone,Cloud Service, | en |
| dc.relation.page | 32 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2013-08-20 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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