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Optically Interrogated Unique Object with Simulation Attack Prevention

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

Published
Publication date25/03/2019
Host publication2019 Design, Automation & Test in Europe Conference & Exhibition (DATE)
PublisherIEEE
Pages198-203
Number of pages6
ISBN (electronic)9783981926323, 9783981926330
ISBN (print)9781728103310
<mark>Original language</mark>English
EventDesign, Automation and Test in Europe - Florence, Italy
Duration: 25/03/201929/03/2019
https://www.date-conference.com

Conference

ConferenceDesign, Automation and Test in Europe
Abbreviated titleDATE
Country/TerritoryItaly
CityFlorence
Period25/03/1929/03/19
Internet address

Conference

ConferenceDesign, Automation and Test in Europe
Abbreviated titleDATE
Country/TerritoryItaly
CityFlorence
Period25/03/1929/03/19
Internet address

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.

Bibliographic note

©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.