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Collusion detection using predictive functions based on android applications

Author(s)
Asad Hameed Soomro Department of Computer Science, Shah Abdul Latif University, Khairpur Mirs, Pakistan
Samina Rajper Department of Computer Science, Shah Abdul Latif University, Khairpur Mirs, Pakistan
Aurangzeb Magsi Department of Computer Science, Shah Abdul Latif University, Khairpur Mirs, Pakistan
Samar Abbas Mangi Department of Computer Science, Shah Abdul Latif University, Khairpur Mirs, Pakistan
Aneela Jan Soomro Computer Department, Government College for Women Khairpur Mirs,,Pakistan
Abstract
Android is used by most of the population of the users. It is an attractive target for malicious application developers due to its open-source nature. A number of applications are developing day by day for android devices to serve the purpose of data stealing activity. A collision attack is one of the types of applications or programs used for data stealing from android devices. During this attack, different apps communicate via Inter-Process Communication (IPC) for a variety of purposes. In this paper, a dynamic approach is proposed for automatic collision detection between communications among different applications. The focus of the study is on the sharing of multiple data types. Moreover, to select applications for analysis is a difficult task to perform and two predictive functions have been used in this regard. The evaluation is performed on a dataset of 800 android applications for analyzing the colluding couples. The developed methodology produces an accuracy of 97.2% during the experiments by the developed system.
Publication Details
Page(s) 15-26
DOI DOI not available
Published Journal: Sukkur IBA Journal of Computing and Mathematical Sciences, Volume: 6, Issue: 2, Year: 2022

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Keywords
Security, android, Predictive function, Formal Model, Collision Detection
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