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MobiLogLeak: A Preliminary Study on Data Leakage Caused by Poor Logging Practices

  • Rui Zhou
  • , Mohammad Hamdaqa
  • , Haipeng Cai
  • , Abdelwahab Hamou-Lhadj
  • Concordia University
  • Reykjavík University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

Logging is an essential software practice that is used by developers to debug, diagnose and audit software systems. Despite the advantages of logging, poor logging practices can potentially leak sensitive data. The problem of data leakage is more severe in applications that run on mobile devices, since these devices carry sensitive identification information ranging from physical device identifiers (e.g., IMEI MAC address) to communications network identifiers (e.g., SIM, IP, Bluetooth ID), and application-specific identifiers related to the location and the users' accounts. This preliminary study explores the impact of logging practices on data leakage of such sensitive information. Particularly, we want to investigate whether log-related statements inserted into an application code could lead to data leakage. While studying logging practices in mobile applications is an active research area, to our knowledge, this is the first study that explores the interplay between logging and security in the context of mobile applications for Android. We propose an approach called MobiLogLeak, an approach that identifies log statements in deployed apps that leak sensitive data. MobiLogLeak relies on taint flow analysis. Among 5,000 Android apps that we studied, we found that 200 apps leak sensitive data through logging.

Original languageEnglish
Title of host publicationSANER 2020 - Proceedings of the 2020 IEEE 27th International Conference on Software Analysis, Evolution, and Reengineering
EditorsKostas Kontogiannis, Foutse Khomh, Alexander Chatzigeorgiou, Marios-Eleftherios Fokaefs, Minghui Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages577-581
Number of pages5
ISBN (Electronic)9781728151434
DOIs
StatePublished - Feb 2020
Event27th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2020 - London, Canada
Duration: Feb 18 2020Feb 21 2020

Publication series

NameSANER 2020 - Proceedings of the 2020 IEEE 27th International Conference on Software Analysis, Evolution, and Reengineering

Conference

Conference27th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2020
Country/TerritoryCanada
CityLondon
Period02/18/2002/21/20

Keywords

  • Data Leakage
  • Logging Practices
  • Mobile Applications
  • Taint Flow Analysis

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