Analyzing Android App Privacy With GP-PP Model
Mobile devices have become the major platforms of the Internet of Things applications for industrial enterprises. The ever-increasing number of Android Phone users has raised great concerns regarding the privacy issues related to the use of Android Apps. Freely downloadable apps requesting a large n...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8395277/ |
| _version_ | 1831669567966937088 |
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| author | Nishtha Kesswani Hongbo Lyu Zuopeng Zhang |
| author_facet | Nishtha Kesswani Hongbo Lyu Zuopeng Zhang |
| author_sort | Nishtha Kesswani |
| collection | DOAJ |
| description | Mobile devices have become the major platforms of the Internet of Things applications for industrial enterprises. The ever-increasing number of Android Phone users has raised great concerns regarding the privacy issues related to the use of Android Apps. Freely downloadable apps requesting a large number of permissions have resulted in severe privacy concerns. While granting the permissions, users usually do not read their details or are unable to judge an app based on the permissions requested. In this paper, we address the privacy issues by categorizing app permissions into privacy invasive and generic permissions and validating the classification using the Naïve Bayes classifier. |
| first_indexed | 2024-12-19T23:01:47Z |
| format | Article |
| id | doaj.art-73dfa31e48a943ec9f21fed0c018ba45 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T23:01:47Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-73dfa31e48a943ec9f21fed0c018ba452022-12-21T20:02:28ZengIEEEIEEE Access2169-35362018-01-016395413954610.1109/ACCESS.2018.28500608395277Analyzing Android App Privacy With GP-PP ModelNishtha Kesswani0Hongbo Lyu1Zuopeng Zhang2https://orcid.org/0000-0002-4074-9505Department of Computer Science, Central University of Rajasthan, Ajmer, IndiaCollege of Logistics and E-Commerce, Zhejiang Wanli University, Ningbo, ChinaSchool of Business and Economics, State University of New York, Plattsburgh, NY, USAMobile devices have become the major platforms of the Internet of Things applications for industrial enterprises. The ever-increasing number of Android Phone users has raised great concerns regarding the privacy issues related to the use of Android Apps. Freely downloadable apps requesting a large number of permissions have resulted in severe privacy concerns. While granting the permissions, users usually do not read their details or are unable to judge an app based on the permissions requested. In this paper, we address the privacy issues by categorizing app permissions into privacy invasive and generic permissions and validating the classification using the Naïve Bayes classifier.https://ieeexplore.ieee.org/document/8395277/Application softwaremobile computingprivacy |
| spellingShingle | Nishtha Kesswani Hongbo Lyu Zuopeng Zhang Analyzing Android App Privacy With GP-PP Model IEEE Access Application software mobile computing privacy |
| title | Analyzing Android App Privacy With GP-PP Model |
| title_full | Analyzing Android App Privacy With GP-PP Model |
| title_fullStr | Analyzing Android App Privacy With GP-PP Model |
| title_full_unstemmed | Analyzing Android App Privacy With GP-PP Model |
| title_short | Analyzing Android App Privacy With GP-PP Model |
| title_sort | analyzing android app privacy with gp pp model |
| topic | Application software mobile computing privacy |
| url | https://ieeexplore.ieee.org/document/8395277/ |
| work_keys_str_mv | AT nishthakesswani analyzingandroidappprivacywithgpppmodel AT hongbolyu analyzingandroidappprivacywithgpppmodel AT zuopengzhang analyzingandroidappprivacywithgpppmodel |