Title: Techniques to detect data leakage in mobile applications

Authors: Thiago Rocha; Eduardo Souto; Khalil El-Khatib

Addresses: FPF TECH, Av Danilo de Matos Areosa, 1170 – Distrito Industrial, Manaus, 69075-351, Brazil ' Institute of Computing, Federal University of Amazonas, Manaus, 69067-005, Brazil ' Advanced Network Technology and Security, University of Ontario Institute of Technology, Oshawa, L1G 0C5, Canada

Abstract: The popularity of mobile devices has skyrocketed over the past few years and has consequently given rise to various attacks in mobile platforms. The most serious among these threats is data leakage as most devices store sensitive information about their users, including location, bank information, to list a few. There have been a large number of data leakage detection proposals for mobile platforms, and a number of researches have looked at specific aspects of the mobile environment and used several techniques to provide protection. This survey provides an analysis of the data leakage problem, explains what it is, what kind of data it can expose, and the main techniques that have been used to circumvent this problem. It also looks at these various individual efforts and grouped them into categories. We also discuss the strengths and shortcomings of these efforts. Finally, some future works and opportunities of research are presented.

Keywords: data leakage; mobile applications; security; mobile devices; Android; taint tracking; machine learning.

DOI: 10.1504/IJSN.2019.101414

International Journal of Security and Networks, 2019 Vol.14 No.3, pp.146 - 157

Received: 07 Feb 2019
Accepted: 07 Feb 2019
Published online: 07 Aug 2019 *

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