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Remote detection of Unauthorized Activity via Spectral Analysis

ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS 2018年第6期23卷 1–21页

作者： Karabacak, Fatih Ogras, Umit Ozev, Sule Arizona State Univ Tempe AZ 85281 USA Intel 5000 W Chandler Blvd Chandler AZ 85226 USA Arizona State Univ ISTB4 Tempe AZ 85281 USA

Unauthorized hardware or firmware modifications, known as trojans, can steal information, drain the battery, or damage IoT devices. Since trojans may be triggered in the field at an unknown instance, it is important to detect their presence at runtime. However, it is difficult to run sophisticated detection algorithms on these devices due to limited computational power and energy and, in some cases, lack of accessibility. This article presents a stand-off self-referencing technique for detecting unauthorized activity. The proposed technique processes involuntary electromagnetic emissions on a separate hardware, which is physically decoupled from the device under test. When the device enters the test mode, a predefined test application is run on the device repetitively for a known period. The periodicity ensures that the spectral electromagnetic power of the test application concentrates at known frequencies, leaving the remaining frequencies within the operating bandwidth at the noise level. Any deviations from the noise level for these unoccupied frequency locations indicate the presence of unknown (unauthorized) activity. Hence, we are able to differentiate trojan activity without using a golden reference, or any knowledge of the attributes of the trojan activity. Experiments based on hardware measurements show that the proposed technique achieves close to 100% detection accuracy at up to 120cm distance.

关键词： IoT security hardware/firmware trojan detection EM emission

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Work-in-Progress: Remote detection of Unauthorized Activity via Spectral Analysis 12

Work-in-Progress: Remote Detection of Unauthorized Activity ...

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International Conference on hardware/Software Codesign and System Synthesis (CODES+ISSS)

作者： Karabacak, Fatih Ogras, Umit Ozev, Sule Arizona State Univ Sch ECEE Tempe AZ 85281 USA

ISBN: (纸本)9781450351850

Unauthorized hardware or firmware modifications, known as trojans, can steal information, drain the battery, or damage IoT devices. This paper presents a stand-off self-referencing technique for detecting unauthorized activity. The proposed technique processes involuntary electromagnetic emissions on a separate hardware, which is physically decoupled from the device under test. When the device enter the test mode, it runs a predefined application repetitively with a fixed period. The periodicity ensures that the spectral electromagnetic power of the test application concentrates at known frequencies, leaving the remaining frequencies within the operation bandwidth at the noise level. Any deviations from the noise level for these unoccupied frequency locations indicates the presence of unknown (unauthorized) activity. Experiments based on hardware measurements show that the proposed technique achieves close to 100% detection accuracy at up to 120 cm distance.

关键词： IoT Security hardware/firmware trojan detection EM Emission

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Remote detection of unauthorized activity via spectral analysis: work-in-progress 17

Remote detection of unauthorized activity via spectral analy...

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Proceedings of the Twelfth IEEE/ACM/IFIP International Conference on hardware/Software Codesign and System Synthesis Companion

作者： Fatih Karabacak Umit Ogras Sule Ozev Arizona State University

ISBN: (纸本)9781450351850

关键词： EM emission hardware/firmware trojan detection IoT security

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