Simandro-plus: On computing similarity of android applicationsopen access
- Authors
- Hamedani, Masoud Reyhani; Kim, Sang-Wook
- Issue Date
- Sep-2021
- Publisher
- COMSIS CONSORTIUM
- Keywords
- android applications; apps data mining; feature extraction; API calls; manifest information; similarity computation
- Citation
- COMPUTER SCIENCE AND INFORMATION SYSTEMS, v.18, no.4, pp.1219 - 1238
- Indexed
- SCIE
SCOPUS
- Journal Title
- COMPUTER SCIENCE AND INFORMATION SYSTEMS
- Volume
- 18
- Number
- 4
- Start Page
- 1219
- End Page
- 1238
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/140975
- DOI
- 10.2298/CSIS210208036H
- ISSN
- 1820-0214
- Abstract
- In this paper, we propose SimAndro-Plus as an improved variant of the state-of-the-art method, SimAndro, to compute the similarity of Android applications (apps) regarding their functionalities. SimAndro-Plus has two major differences with SimAndro: 1) it exploits two beneficial features to similarity computa-tion, which are totally disregarded by SimAndro; 2) to compute the similarity score of an app-pair based on strings and package name features, SimAndro-Plus considers not only those terms co-appearing in both apps but also considers those terms appearing in one app while missing in the other one. The results of our extensive ex-periments with three real-world datasets and a dataset constructed by human experts demonstrate that 1) each of the two aforementioned differences is really effective to achieve better accuracy and 2) SimAndro-Plus outperforms SimAndro in similarity computation by 14% in average.
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