Visible to the public Optically Interrogated Unique Object with Simulation Attack Prevention

TitleOptically Interrogated Unique Object with Simulation Attack Prevention
Publication TypeConference Paper
Year of Publication2019
AuthorsMarcinkevicius, Povilas, Bagci, Ibrahim Ethem, Abdelazim, Nema M., Woodhead, Christopher S., Young, Robert J., Roedig, Utz
Conference Name2019 Design, Automation Test in Europe Conference Exhibition (DATE)
Date Publishedmar
Keywordsabsorption, Adaptive optics, analogue measurement, Cameras, composability, Computer simulation, confinement, Cyber-physical systems, data protection, Entropy, light sources, Nonlinear optics, photoconductive cells, photoluminescence, physical object, privacy, pubcrawl, quantum computing, Quantum Confinement UNO responds, Quantum dots, resilience, Resiliency, security of data, semiconductor quantum dots, simulation attack, simulation attack prevention, simulation attack protection, simulation attacks, unique object, unique photo-luminescence properties, UNO
AbstractA 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.
Citation Keymarcinkevicius_optically_2019