Using unique surface patterns of injection moulded plastic components as an image based Physical Unclonable Function for secure component identification

Wigger, Benedikt; Meißner, Thomas; Förste, Alexander; Jetter, Volker; Zimmermann, André

doi:10.1038/s41598-018-22876-8

Cited by 21 publications

(24 citation statements)

References 19 publications

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“…In the RF‐DNA‐PUF, DeJean and Kirovski [22] built a group of antennas that works as RF transmitters or receivers for collecting the scattering parameters caused by different constellations of dielectric or conductive objects between the transmitters and the receiver antennas. Wigger , et al [23] proposed image‐based PUF (I‐PUF) where the author used a camera to capture surface patterns of injection moulded plastic components that are used for identification. Computational O‐PUF (CO‐PUF) is presented by Birch , et al [24].…”

Section: Literature Reviewmentioning

confidence: 99%

Physical unclonable function: architectures, applications and challenges for dependable security

Ning

Farha

Ullah

et al. 2020

IET Circuits, Devices & Systems

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Physical unclonable function (PUF) is hardware-specific security primitive for providing cryptographic functionalities that are applicable for secure communication among the embedded devices. The physical structure of PUF is considered to be easy to manufacture but hard or impossible to replicate due to variations in its manufacturing process. However, a large community of analytics believes hardware-based PUF has paved the way for its realisation in providing dependable security. In this study, the authors have thoroughly explored the architecture, applications, requirements, and challenges of PUF that provide security solutions. For presenting the literature, they have designed a taxonomy where PUFs are divided under two main categories, including non-silicon and silicon-based PUF. Currently, there is no comprehensive survey that highlights the comparison and usability of memory-based and analogue/mixed-signal based PUF that are considered to be suitable as compared to counterparts. In a similar vein, they have presented the network-specific application scenarios in wireless sensor network, wireless body area network and Internet of Things and then identified the strong, weak and controlled PUF in a categorical manner. Moreover, they have presented a number of prospective limitations that are identified in PUF structures and then identified the open research challenges to meet the desired security levels.

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Section: Literature Reviewmentioning

confidence: 99%

Physical unclonable function: architectures, applications and challenges for dependable security

Ning

Farha

Ullah

et al. 2020

IET Circuits, Devices & Systems

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“…UNOs based on different materials have been proposed such as paper fibers [4], physical irregularities on CDs [5], patterns appearing on plates of specific plastics [6], and many more [7], [8], [9]. Baiet al [12] use Quantum Dots (QDs) to create spectral bar-codes.…”

Section: Related Workmentioning

confidence: 99%

“…Existing work mostly does not consider such practical aspects. For example, existing work such as [6], [7], [9] does not discuss device behaviour in presence of errors. The QCUNO also discusses simulation attack detection and resistance which other proposed solutions such as [5], [6], [7], [9] do not discuss.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Optically Interrogated Unique Object with Simulation Attack Prevention

Marcinkevicius

Bağcı

Abdelazim

et al. 2019

2019 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE)

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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.

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“…An image-based PUF using imagery from injection moulded plastic for anti-counterfeiting purposes was introduced by Wigger et al [38]. A database of 200 samples from two different injection moulded materials (100 + 100) was used to demonstrate the effectiveness of using the surface patterns for individual object recognition.…”

mentioning

confidence: 99%

Cork as a Unique Object: Device, Method, and Evaluation

2018

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Unique Objects (UNOs) are relevant for real-world applications such as anti-counterfeiting systems. In this work, cork is demonstrated as a UNO, part of the Physical Unclonability and Disorder (PUD) system. An adequate measurement kit (illumination device) and recognition method are also devised and evaluated. Natural hills and valleys of the cork are enhanced using the illumination device and the overall robustness of the recognition application inherent to UNOs is presented. The lighting device is based on grazing light and the recognition task is based on a local feature detector and descriptor called ORB - Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features). The performance evaluation utilizes a private cork database (1500 photos of 500 cork stoppers) and three public iris databases. In the tests carried out on the illumination device, the results clearly show the success of capturing stable/repeatable features needed for the recognition task in the cork database. This achievement is also reflected in the perfect recognition score achieved in the cork database, in the intra-distance measure μ i n t r a , which gives the notion of average noise between measures, and in the inter-distance μ i n t e r which provides hints about the randomness/uniqueness of a cork. Regarding the recognition application, its effectiveness is further tested using the iris databases. Regardless of the fact that the recognition algorithm was not designed for the iris recognition problem, the results show that the proposed approach is capable of competing with the techniques found in the literature specially designed for iris recognition. Furthermore, the evaluation shows that the three requirements that constitute a UNO (Disorder, Operability, and Unclonability) are fulfilled, thus supporting the main assertion of this work: that cork is a UNO.

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Using unique surface patterns of injection moulded plastic components as an image based Physical Unclonable Function for secure component identification

Cited by 21 publications

References 19 publications

Physical unclonable function: architectures, applications and challenges for dependable security

Physical unclonable function: architectures, applications and challenges for dependable security

Optically Interrogated Unique Object with Simulation Attack Prevention

Cork as a Unique Object: Device, Method, and Evaluation

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