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LazyTainter: Memory-Efficient Taint Tracking in Managed Runtimes

Published: 07 November 2014 Publication History

Abstract

The leakage of private information is of great concern on mobile devices since they contain a great deal of sensitive information. This has spurred interest in the use of taint tracking systems to track and monitor the flow of private information on a mobile device. Taint tracking systems impose memory overhead, as taint information must be maintained for every piece of information an application stores in memory. This memory cost is at odds with the growing number of low-end, memory-constrained devices, which makes up the majority mobile device growth in emerging markets. To make taint tracking affordable and to benefit a broader range of mobile devices, we present LazyTainter, which is a memory-efficient taint tracking system designed for managed runtimes. To implement LazyTainter, we enhanced TaintDroid with hybrid taint tracking, which combines lazy and eager tainting, to reduce memory usage with only negligible performance loss. Our experimental results demonstrate that LazyTainter can reduce heap usage by as much as 26.5% when compared to TaintDroid while imposing a negligible 1% increase in performance overhead.

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  • (2020)Maybe tainted data: Theory and a case studyJournal of Computer Security10.3233/JCS-191342(1-41)Online publication date: 1-Apr-2020
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  1. LazyTainter: Memory-Efficient Taint Tracking in Managed Runtimes

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      cover image ACM Conferences
      SPSM '14: Proceedings of the 4th ACM Workshop on Security and Privacy in Smartphones & Mobile Devices
      November 2014
      118 pages
      ISBN:9781450331555
      DOI:10.1145/2666620
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 07 November 2014

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      Author Tags

      1. android
      2. memory efficiency
      3. taint tracking

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      SPSM '14 Paper Acceptance Rate 11 of 29 submissions, 38%;
      Overall Acceptance Rate 46 of 139 submissions, 33%

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      Cited By

      View all
      • (2020)Maybe tainted data: Theory and a case studyJournal of Computer Security10.3233/JCS-191342(1-41)Online publication date: 1-Apr-2020
      • (2019)Reducing Security Risks of Suspicious Data and Codes Through a Novel Dynamic Defense ModelIEEE Transactions on Information Forensics and Security10.1109/TIFS.2019.290179814:9(2427-2440)Online publication date: Sep-2019
      • (2018)A New Method of Live Tracking of Process MemoryProceedings of the 2nd International Conference on Cryptography, Security and Privacy10.1145/3199478.3199497(154-158)Online publication date: 16-Mar-2018
      • (2017)Quantitave Dynamic Taint Analysis of Privacy Leakage in Android Arabic AppsProceedings of the 12th International Conference on Availability, Reliability and Security10.1145/3098954.3105827(1-9)Online publication date: 29-Aug-2017
      • (2017)A Taxonomy and Qualitative Comparison of Program Analysis Techniques for Security Assessment of Android SoftwareIEEE Transactions on Software Engineering10.1109/TSE.2016.261530743:6(492-530)Online publication date: 1-Jun-2017
      • (2016)*droidACM Computing Surveys10.1145/299635849:3(1-30)Online publication date: 21-Oct-2016
      • (2016)On a (Per)MissionProceedings of the 6th Workshop on Security and Privacy in Smartphones and Mobile Devices10.1145/2994459.2994466(63-72)Online publication date: 24-Oct-2016
      • (2016)In-Depth Enforcement of Dynamic Integrity Taint AnalysisProceedings of the 2016 ACM Workshop on Programming Languages and Analysis for Security10.1145/2993600.2993610(43-56)Online publication date: 24-Oct-2016
      • (2016)Call Me Back!Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security10.1145/2976749.2978342(92-103)Online publication date: 24-Oct-2016
      • (2016)Data leakage detection in Tizen Web applications2016 14th Annual Conference on Privacy, Security and Trust (PST)10.1109/PST.2016.7906994(608-614)Online publication date: Dec-2016

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