Exploring electrospun nanofibers for physically unclonable functions: a scalable and robust method toward unique identifiers

Optical physically unclonable functions (PUFs) have great potential in the security identification of the internet of things. In this work, electrospun nanofibers are proposed as a candidate for a nanoscale, robust, stable and scalable PUF. The dark-field reflectance images of the polymer fibers are quantitatively analyzed by the Hough transform. We find that the fiber length and orientation distribution reach an optimal point as the fiber density (number of fibers detected by Hough ttansform) grows up over 850 in 400 × 400 pixels for a polyvinylpyrrolidone (PVP) nanofiber-based PUF device. Subsequently, we test the robustness and randomness of the PUF pattern by using the fiber amount as an encoding feature, generating a reconstruction success rate of over 80% and simultaneously an entropy of 260 bits within a mean size of 4 cm2. A scale-invariant algorithm is adopted to identify the uniqueness of each pattern on a 256-sensor device. Furthermore, the thermo-, moisture and photostability of the authentication process are systematically investigated by comparing the polyacrylonitrile to the PVP system.

[1]  N. Karmakar,et al.  Chipless RFID Printing Technologies: A State of the Art , 2021, IEEE Microwave Magazine.

[2]  Wook Park,et al.  Gradient-Wrinkled Microparticle with Grayscale Lithography Controlling the Cross-Linking Densities for High Security Level Anti-Counterfeiting Strategies , 2021, ACS omega.

[3]  Hui Yang,et al.  Facile preparation of patterned silver electrodes with high conductivity, flatness and adjustable work function by laser direct writing followed by transfer process , 2020 .

[4]  J. Fleischer,et al.  Fiber orientation measurement of fiber injection molded nonwovens by image analysis , 2020 .

[5]  D. Descamps,et al.  Laser Generation of Sub‐Micrometer Wrinkles in a Chalcogenide Glass Film as Physical Unclonable Functions , 2020, Advanced materials.

[6]  Paul S. Francis,et al.  Plasmonic nanopapers: flexible, stable and sensitive multiplex PUF tags for unclonable anti-counterfeiting applications. , 2020, Nanoscale.

[7]  Feng Li,et al.  Temporal Multilevel Luminescence Anti-Counterfeiting through Scattering Media. , 2020, ACS nano.

[8]  Li Lin,et al.  Gap-enhanced Raman tags for physically unclonable anticounterfeiting labels , 2020, Nature Communications.

[9]  Jun Hee Lee,et al.  Enhanced Moisture Stability by Butyldimethylsulfonium Cation in Perovskite Solar Cells , 2019, Advanced science.

[10]  U. Bach,et al.  Self-assembly of coordination polymers on plasmonic surfaces for computer vision decodable, unclonable and colorful security labels , 2019, Journal of Materials Chemistry C.

[11]  Mehdi Ezoji,et al.  Average fiber diameter measurement in Scanning Electron Microscopy images based on Gabor filtering and Hough transform , 2019, Measurement.

[12]  Gungun Lin,et al.  Optical Nanomaterials and Enabling Technologies for High‐Security‐Level Anticounterfeiting , 2019, Advanced materials.

[13]  Yang Li,et al.  Inkjet-printed unclonable quantum dot fluorescent anti-counterfeiting labels with artificial intelligence authentication , 2019, Nature Communications.

[14]  Xuesong Jiang,et al.  Pattern Memory Surface (PMS) with Dynamic Wrinkles for Unclonable Anticounterfeiting , 2019, ACS Materials Letters.

[15]  Daniel Granados,et al.  Physically Unclonable Functions Based on Single-Walled Carbon Nanotubes: A Scalable and Inexpensive Method toward Unique Identifiers , 2019, ACS Applied Nano Materials.

[16]  Yang Lu,et al.  Internet of Things (IoT) Cybersecurity Research: A Review of Current Research Topics , 2019, IEEE Internet of Things Journal.

[17]  Younan Xia,et al.  Electrospinning and Electrospun Nanofibers: Methods, Materials, and Applications. , 2019, Chemical reviews.

[18]  Xia Li,et al.  Review on Optical Image Hiding and Watermarking Techniques , 2018, Optics & Laser Technology.

[19]  Volker Jetter,et al.  Using unique surface patterns of injection moulded plastic components as an image based Physical Unclonable Function for secure component identification , 2018, Scientific Reports.

[20]  Weidong Yu,et al.  Orientation image analysis of electrospun submicro-fibers based on Hough transform and Regionprops function , 2017 .

[21]  Thomas Just Sørensen,et al.  Physical unclonable functions generated through chemical methods for anti-counterfeiting , 2017 .

[22]  Bin Yu,et al.  The influence of process parameters on needle punched nonwovens investigated using image analysis , 2017 .

[23]  Gabriele Lenzini,et al.  High-fidelity spherical cholesteric liquid crystal Bragg reflectors generating unclonable patterns for secure authentication , 2016, Scientific Reports.

[24]  S. Skrabalak,et al.  Plasmonic Nanoparticles as a Physically Unclonable Function for Responsive Anti‐Counterfeit Nanofingerprints , 2016 .

[25]  Lingfeng Liu,et al.  On Nonlinear Complexity and Shannon's Entropy of Finite Length Random Sequences , 2015, Entropy.

[26]  Yun-Ze Long,et al.  Advances in three-dimensional nanofibrous macrostructures via electrospinning , 2014 .

[27]  Andrew Beng Jin Teoh,et al.  Analysis of correlation of 2DPalmHash Code and orientation range suitable for transposition , 2014, Neurocomputing.

[28]  Dexing Zhong,et al.  Fingerprint Identification Using SIFT-Based Minutia Descriptors and Improved All Descriptor-Pair Matching , 2013, Sensors.

[29]  Laurent Jacques,et al.  Analysis and experimental evaluation of image-based PUFs , 2012, Journal of Cryptographic Engineering.

[30]  Helena Handschuh,et al.  Efficient Implementation of True Random Number Generator Based on SRAM PUFs , 2012, Cryptography and Security.

[31]  Li Zan,et al.  New complexity metric of chaotic pseudorandom sequences using fuzzy relationship entropy , 2011 .

[32]  Jean-Jacques Quisquater,et al.  How to strongly link data and its medium: the paper case , 2010, IET Inf. Secur..

[33]  B. Burgeth,et al.  Determination of the fibre orientation in composites using the structure tensor and local X-ray transform , 2010 .

[34]  S. Kalidindi,et al.  Applications of the Phase-Coded Generalized Hough Transform to Feature Detection, Analysis, and Segmentation of Digital Microstructures , 2009 .

[35]  A. Ajji,et al.  Color-changing and color-tunable photonic bandgap fiber textiles. , 2008, Optics express.

[36]  Sharath Pankanti,et al.  Fingerprint verification using SIFT features , 2008, SPIE Defense + Commercial Sensing.

[37]  Behnam Pourdeyhimi,et al.  Measuring Fiber Orientation in Nonwovens: The Hough Transform , 2002 .

[38]  Anil K. Jain,et al.  Fingerprint Image Enhancement: Algorithm and Performance Evaluation , 1998, IEEE Trans. Pattern Anal. Mach. Intell..