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Optically Interrogated Unique Object with Simulation Attack Prevention

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Optically Interrogated Unique Object with Simulation Attack Prevention. / Marcinkevicius, Povilas; Bagci, Ibrahim Ethem; Abdelazim, Nema Mohamed Safwat Ibrahim; Woodhead, Christopher Stephen; Young, Robert James; Roedig, Utz.

2019 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2019. p. 198-203.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

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Marcinkevicius, P, Bagci, IE, Abdelazim, NMSI, Woodhead, CS, Young, RJ & Roedig, U 2019, Optically Interrogated Unique Object with Simulation Attack Prevention. in 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, pp. 198-203, Design, Automation and Test in Europe, Florence, Italy, 25/03/19. https://doi.org/10.23919/DATE.2019.8715151

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@inproceedings{4217151610f5481198a8afa8edc9d89e,
title = "Optically Interrogated Unique Object with Simulation Attack Prevention",
abstract = "A Unique Object (UNO) is a physical object with unique characteristics that can be measured externally. The usually analogue measurement can be converted into a digital representation - a fingerprint - which uniquely identifies the object. For practical applications it is necessary that measurements can be performed without the need of specialist equipment or complex measurement setup. Furthermore, a UNO should be able to defeat simulation attacks; an attacker may replace the UNO with a device or system that produces the expected measurement. Recently a novel type of UNOs based on Quantum Dots (QDs) and exhibiting unique photo-luminescence properties has been proposed. The uniqueness of these UNOs is based on quantum effects that can be interrogated using a light source and a camera. The so called Quantum Confinement UNO (QCUNO) responds uniquely to different light excitation levels which is exploited for simulation attack protection, as opposed to focusing on features too small to reproduce and therefore difficult to measure. In this paper we describe methods for extraction of fingerprints from the QCUNO. We evaluate our proposed methods using 46 UNOs in a controlled setup. Focus of the evaluation are entropy, error resilience and the ability to detect simulation attacks.",
author = "Povilas Marcinkevicius and Bagci, {Ibrahim Ethem} and Abdelazim, {Nema Mohamed Safwat Ibrahim} and Woodhead, {Christopher Stephen} and Young, {Robert James} and Utz Roedig",
note = "{\textcopyright}2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.; Design, Automation and Test in Europe, DATE ; Conference date: 25-03-2019 Through 29-03-2019",
year = "2019",
month = mar
day = "25",
doi = "10.23919/DATE.2019.8715151",
language = "English",
isbn = "9781728103310",
pages = "198--203",
booktitle = "2019 Design, Automation & Test in Europe Conference & Exhibition (DATE)",
publisher = "IEEE",
url = "https://www.date-conference.com",

}

RIS

TY - GEN

T1 - Optically Interrogated Unique Object with Simulation Attack Prevention

AU - Marcinkevicius, Povilas

AU - Bagci, Ibrahim Ethem

AU - Abdelazim, Nema Mohamed Safwat Ibrahim

AU - Woodhead, Christopher Stephen

AU - Young, Robert James

AU - Roedig, Utz

N1 - ©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2019/3/25

Y1 - 2019/3/25

N2 - A Unique Object (UNO) is a physical object with unique characteristics that can be measured externally. The usually analogue measurement can be converted into a digital representation - a fingerprint - which uniquely identifies the object. For practical applications it is necessary that measurements can be performed without the need of specialist equipment or complex measurement setup. Furthermore, a UNO should be able to defeat simulation attacks; an attacker may replace the UNO with a device or system that produces the expected measurement. Recently a novel type of UNOs based on Quantum Dots (QDs) and exhibiting unique photo-luminescence properties has been proposed. The uniqueness of these UNOs is based on quantum effects that can be interrogated using a light source and a camera. The so called Quantum Confinement UNO (QCUNO) responds uniquely to different light excitation levels which is exploited for simulation attack protection, as opposed to focusing on features too small to reproduce and therefore difficult to measure. In this paper we describe methods for extraction of fingerprints from the QCUNO. We evaluate our proposed methods using 46 UNOs in a controlled setup. Focus of the evaluation are entropy, error resilience and the ability to detect simulation attacks.

AB - A Unique Object (UNO) is a physical object with unique characteristics that can be measured externally. The usually analogue measurement can be converted into a digital representation - a fingerprint - which uniquely identifies the object. For practical applications it is necessary that measurements can be performed without the need of specialist equipment or complex measurement setup. Furthermore, a UNO should be able to defeat simulation attacks; an attacker may replace the UNO with a device or system that produces the expected measurement. Recently a novel type of UNOs based on Quantum Dots (QDs) and exhibiting unique photo-luminescence properties has been proposed. The uniqueness of these UNOs is based on quantum effects that can be interrogated using a light source and a camera. The so called Quantum Confinement UNO (QCUNO) responds uniquely to different light excitation levels which is exploited for simulation attack protection, as opposed to focusing on features too small to reproduce and therefore difficult to measure. In this paper we describe methods for extraction of fingerprints from the QCUNO. We evaluate our proposed methods using 46 UNOs in a controlled setup. Focus of the evaluation are entropy, error resilience and the ability to detect simulation attacks.

U2 - 10.23919/DATE.2019.8715151

DO - 10.23919/DATE.2019.8715151

M3 - Conference contribution/Paper

SN - 9781728103310

SP - 198

EP - 203

BT - 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE)

PB - IEEE

T2 - Design, Automation and Test in Europe

Y2 - 25 March 2019 through 29 March 2019

ER -