Trusted detection of sensitive activities on mobile phones using power consumption measurements

Mordechai Guri, Gabi Kedma, Boris Zadov, Yuval Elovici

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

3 Scopus citations

Abstract

The unprecedented popularity of modern mobile phones has made them a lucrative target for skillful and motivated offenders. A typical mobile phone is packed with sensors, which can be turned on silently by a malicious program, providing invaluable information to the attacker. Detecting such hidden activities through software monitors can be blindfolded and bypassed by rootkits and by anti-forensic methods applied by the malicious program. Moreover, detecting power consumption by software running on the mobile phone is susceptible to similar evasive techniques. Consequently, software based detection of hidden malicious activities, particularly the silent activation of sensors, cannot be considered as trusted. In this paper we present a method which detects hidden activities using external measurement of power consumption. The classification model is acquired using machine-learning multi-label classification algorithms. Our method overcomes the inherent weaknesses of software-based monitors, and provides a trusted solution. We describe the measurement setup, and provide detailed evaluation results of the algorithms used. The results obtained so far support the feasibility of our method.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages145-151
Number of pages7
ISBN (Electronic)9781479963645
DOIs
StatePublished - 4 Dec 2014
Event2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014 - The Hague, Netherlands
Duration: 24 Sep 201426 Sep 2014

Publication series

NameProceedings - 2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014

Conference

Conference2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014
Country/TerritoryNetherlands
CityThe Hague
Period24/09/1426/09/14

Keywords

  • Machine learning
  • Mobile phone security
  • Multi-label classification
  • Trusted measurement

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Software

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