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MagAttack: remote app sensing with your phone

Published: 12 September 2016 Publication History

Abstract

By tracking changes in electromagnetic radiation footprint emitted from computers using a magnetometer on commodity mobile devices, a malicious attacker can easily learn the secrets of the computer's owner without physically peeping at or hacking into the victim's system. Targeting at Applications and Web browsers, we present MagAttack, which uses the built-in magnetometer on commodity mobile phones to infer which App is running or which webpage the user is browsing on a nearby computer, as well as finer-grained information about victim's interests, habits, etc.
Our preliminary results show that MagAttack is independent of the earth's magnetic filed, model of phones, and magnetometer sampling rates. We also conducted an in-the-wild evaluation where an instrumented participant uses her laptop as usual and MagAttack can detect when she opens 10 different popular Apps. MagAttack achieves a classification accuracy of up to 98%.

References

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Daniel Genkin, Itamar Pipman, and Eran Tromer. 2015. Get your hands off my laptop: Physical side-channel key-extraction attacks on PCs. Journal of Cryptographic Engineering 5, 2 (2015), 95--112.
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Sidhant Gupta, Matthew S Reynolds, and Shwetak N Patel. 2010. ElectriSense: single-point sensing using EMI for electrical event detection and classification in the home. In Proceedings of the 12th ACM international conference on Ubiquitous computing. ACM, 139--148.
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Paul C Kocher. 1996. Timing attacks on implementations of Diffie-Hellman, RSA, DSS, and other systems. In Advances in Cryptology-CRYPTO 1996. Springer, 104--113.
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Yan Michalevsky, Dan Boneh, and Gabi Nakibly. 2014. Gyrophone: Recognizing speech from gyroscope signals. In 23rd USENIX Security Symposium (USENIX Security 14). 1053--1067.
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François Petitjean, Germain Forestier, Geoffrey I Webb, Ann E Nicholson, Yanping Chen, and Eamonn Keogh. 2014. Dynamic time warping averaging of time series allows faster and more accurate classification. In Data Mining (ICDM), 2014 IEEE International Conference on. IEEE, 470--479.
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Cati Vaucelle, Hiroshi Ishii, and Joseph A Paradiso. 2009. Cost-effective wearable sensor to detect EMF. In CHI'09 Extended Abstracts on Human Factors in Computing Systems. ACM, 4309--4314.
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Alenka Zajic and Milos Prvulovic. 2014. Experimental demonstration of electromagnetic information leakage from modern processor-memory systems. Electromagnetic Compatibility, IEEE Transactions on 56, 4 (2014), 885--893.

Cited By

View all
  • (2025)MagSpy: Revealing User Privacy Leakage via Magnetometer on Mobile DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2024.349550624:3(2455-2469)Online publication date: Mar-2025
  • (2024)MagView++: Data Exfiltration via CPU Magnetic Signals Under Video DecodingIEEE Transactions on Mobile Computing10.1109/TMC.2023.326240023:3(2486-2503)Online publication date: Mar-2024
  • (2023)MagneComm+: Near-Field Electromagnetic Induction Communication With MagnetometerIEEE Transactions on Mobile Computing10.1109/TMC.2021.313348122:5(2789-2801)Online publication date: 1-May-2023
  • Show More Cited By

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  1. MagAttack: remote app sensing with your phone

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    Published In

    cover image ACM Conferences
    UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct
    September 2016
    1807 pages
    ISBN:9781450344623
    DOI:10.1145/2968219
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 12 September 2016

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    Author Tags

    1. commodity mobile device
    2. magnetometer
    3. side channel attack

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    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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    Cited By

    View all
    • (2025)MagSpy: Revealing User Privacy Leakage via Magnetometer on Mobile DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2024.349550624:3(2455-2469)Online publication date: Mar-2025
    • (2024)MagView++: Data Exfiltration via CPU Magnetic Signals Under Video DecodingIEEE Transactions on Mobile Computing10.1109/TMC.2023.326240023:3(2486-2503)Online publication date: Mar-2024
    • (2023)MagneComm+: Near-Field Electromagnetic Induction Communication With MagnetometerIEEE Transactions on Mobile Computing10.1109/TMC.2021.313348122:5(2789-2801)Online publication date: 1-May-2023
    • (2021)MagThief: Stealing Private App Usage Data on Mobile Devices via Built-in Magnetometer2021 18th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)10.1109/SECON52354.2021.9491601(1-9)Online publication date: 6-Jul-2021
    • (2020)Leveraging family force to assist adolescent patients in the treatment of technology abuseAdjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers10.1145/3410530.3414391(33-37)Online publication date: 10-Sep-2020
    • (2018)My Magnetometer Is Telling You Where I've Been?Proceedings of the 11th ACM Conference on Security & Privacy in Wireless and Mobile Networks10.1145/3212480.3212502(260-270)Online publication date: 18-Jun-2018

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