Android malware detection using big data analytics techniques
Application clones have been found in many third party markets, which not only make damage to the interest of original application developers, but also pose threats to security and privacy of mobile users. This project implements 3DCFG, which is a centroid-based clone detection method. Experiments o...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/10356/67775 |
| _version_ | 1826122126030012416 |
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| author | Han, Bihui |
| author2 | Chen Lihui |
| author_facet | Chen Lihui Han, Bihui |
| author_sort | Han, Bihui |
| collection | NTU |
| description | Application clones have been found in many third party markets, which not only make damage to the interest of original application developers, but also pose threats to security and privacy of mobile users. This project implements 3DCFG, which is a centroid-based clone detection method. Experiments on 10,000 Android applications demonstrate the effectiveness and scalability of the 3DCFG method. To further improve the detection speed and accuracy, a combination usage of three library detection tools is used to filter third party libraries before clone detection. A clustering-based library detection method proposed from WuKong is implemented and it is used as a library detection tool in 3DCFG library filtering part. |
| first_indexed | 2024-10-01T05:43:42Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/67775 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:43:42Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-10356/677752023-07-07T15:42:14Z Android malware detection using big data analytics techniques Han, Bihui Chen Lihui School of Electrical and Electronic Engineering DRNTU::Engineering Application clones have been found in many third party markets, which not only make damage to the interest of original application developers, but also pose threats to security and privacy of mobile users. This project implements 3DCFG, which is a centroid-based clone detection method. Experiments on 10,000 Android applications demonstrate the effectiveness and scalability of the 3DCFG method. To further improve the detection speed and accuracy, a combination usage of three library detection tools is used to filter third party libraries before clone detection. A clustering-based library detection method proposed from WuKong is implemented and it is used as a library detection tool in 3DCFG library filtering part. Bachelor of Engineering 2016-05-20T06:14:57Z 2016-05-20T06:14:57Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67775 en Nanyang Technological University 53 p. application/pdf |
| spellingShingle | DRNTU::Engineering Han, Bihui Android malware detection using big data analytics techniques |
| title | Android malware detection using big data analytics techniques |
| title_full | Android malware detection using big data analytics techniques |
| title_fullStr | Android malware detection using big data analytics techniques |
| title_full_unstemmed | Android malware detection using big data analytics techniques |
| title_short | Android malware detection using big data analytics techniques |
| title_sort | android malware detection using big data analytics techniques |
| topic | DRNTU::Engineering |
| url | http://hdl.handle.net/10356/67775 |
| work_keys_str_mv | AT hanbihui androidmalwaredetectionusingbigdataanalyticstechniques |