Granularity and detection capability of an adaptive embedded Hardware Trojan detection system

Maxime Lecomte 1 Jacques Jean-Alain Fournier 1 Philippe Maurine 2
1 DPACA [Gardanne]
CEA Tech PACA
2 SysMIC - Conception et Test de Systèmes MICroélectroniques
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : With the outsourcing of the integrated circuit (IC) manufacturing, embedded systems faces threats as Hardware Trojan. This paper presents a characterization of a Hardware Trojan detection method introduced in a former work. In this work, a network of sensors is uniformly spread over the IC surface to monitor locally the inner supply voltage. By conducting an analysis by lot, the authors are able to get rid of the main problem of Hardware Trojan detection: the effect of intra-die and inter-die process variations. In this paper, an analysis of the spatial coverage of the method is made experimentally on a set of FPGA boards. From the obtained results, a modification of the used sensor is proposed as well as an adaptive distinguisher which aims at reducing the false positive rate. These two improvements are also experimentally tested and validated with the same set of FPGA boards.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01434150
Contributor : Caroline Lebrun <>
Submitted on : Friday, January 13, 2017 - 11:07:08 AM
Last modification on : Wednesday, July 17, 2019 - 9:49:12 AM

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Maxime Lecomte, Jacques Jean-Alain Fournier, Philippe Maurine. Granularity and detection capability of an adaptive embedded Hardware Trojan detection system. HOST: Hardware Oriented Security and Trust, May 2016, McLean, VA, United States. pp.135-138, ⟨10.1109/HST.2016.7495571⟩. ⟨lirmm-01434150⟩

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